This article presents a systematic approach for assessing the maturity of manufacturing technologies. A methodology is proposed that is based on modelling the capability of the individual processes and technology interfaces between them. It is inspired by a capability maturity model which has been applied successfully in the field of software engineering. The methodology was developed to assess the maturity levels of individual processes and the combined maturity of pairs or chains of processes. To demonstrate its validity, it was applied for assessing the maturity of technologies in the micro and nano manufacturing domain. The results demonstrated its applicability as a tool for evaluating the maturity of micro and nano manufacturing pairs and their constituent processes. Also, it was shown that the methodology can be employed for identifying process pairs, suitable for integration in process chains, together with their potential weaknesses.
It is still a challenge to machine high-strength carbon fiber–reinforced polymer with high quality due to its poor machinability. Fiber direction is the critical factor. This article aims to investigate the effects of fiber cutting angle in milling of high-strength unidirectional carbon fiber–reinforced polymer laminates with regard to milling forces, machined surface morphology and surface roughness. The edge trimming and slot milling tests were conducted. The largest radial and tangential forces were observed on 135° fiber cutting angle followed by 90° while the smallest milling forces were observed on 45° fiber cutting angle. Totally, four basic material fracture mechanisms, that is, fiber–matrix debonding, bending-induced fiber fracture, shear-induced fiber fracture and compression-induced fiber fracture, were observed by the analysis of fracture morphology for a single fiber. The four basic material fracture mechanisms dominate the material fracture behavior during the cutting of carbon fiber–reinforced polymer. Besides, it is indicated that surface roughness of the machined surfaces is highly related to the type of the surface defects. Surface cavities caused by fiber–matrix debonding and bending-induced fiber fractures on 45° fiber cutting angle were observed to be the main factors leading to the decline of surface finish in milling of carbon fiber–reinforced polymer laminates.
In this article, we consider an imperfect production-inventory system which produces a single type of product to meet the constant demand. The system deteriorates stochastically with usage and the deterioration process is modeled by a non-stationary gamma process. The production process is imperfect which means that the system produces some non-conforming items and the product quality depends on the degradation level of the production system. To prevent the system from deteriorating worse and improve the product quality, preventive maintenance is performed when the level of the system degradation reaches a certain threshold. However, the preventive maintenance is imperfect which cannot restore the system as good as new. Hence, the aging system will be replaced by a new one after some production cycles. The preventive maintenance cost, the replacement cost, the production cost, the inventory holding cost and the penalty cost of lost sales are considered in this article. The objective is to minimize the total cost per unit item which depends on two decision variables: the preventive maintenance threshold and the time at which the system is replaced. We derive the explicit expression of the total cost per unit item and the optimal joint policy can be obtained numerically. An illustrative example and sensitivity analysis are given to demonstrate the proposed model.
The hazard rate curve of the numerical control machine tool is a bathtub curve. The change point between the early failure period and the random failure period of the curve is difficult to obtain with a small data sample; thus, a Bayesian method is proposed. A method to build the prior distributions of the Weibull parameters is developed, which integrates the multi-source prior information of the target numerical control machine tool and the reference numerical control machine tool. The Markov chain Monte Carlo method is adopted to calculate the estimators of the Weibull parameters corresponding to each failure, which solves the problem of the absence of an analytical solution. The total working time of the numerical control machine tool when the estimator of the shape parameter is equal to 1 is estimated by taking the estimator of the shape parameter as the function of time. As a result, the change point and the early failure period are obtained. Comparison result shows that the result obtained through an existing change point solving method with a large dataset is close to the result generated through the proposed method with a small dataset. The change point and the early failure period obtained with the proposed method can be used to guide the early failure test and to design a rational maintenance strategy, which are of vital engineering significance.
The automotive sector, along with many others, has been subject to two key trends in recent times. The first relates to globalization, in other words, the incorporation of new markets and a growing demand that needs to be satisfied. The second concerns the high expectations of customers regarding quality and the on-going renovation of products. The incorporation of new markets results in the expansion of new production centres all over the world, making it necessary to synchronize launches in different parts of the globe. Furthermore, customers’ new demands cause shorter product life cycles. Time is seen as the main factor in the success of any new product launch. Particularly, the period that begins when the production has started in a production plant and continues until the planned production rate has been attained (the ramp-up curve). Because launches have become more frequent, the specific importance given to the life of the model is greater. This article has the following objective: provide a thorough review of the literature, focusing on this specific phase in the life cycle of a model in order to identify, compile and extract any relevant information that will enable us to build a theoretical framework for the ramp-up curve. The article begins by analysing the different interpretations of the phases of the launch stage of a new product that exist in the literature, and it concludes with the evidence that ramp-up curves are an item of scientific interest, where the 21% of the papers relating to this item are focused on the automotive sector, where planning and management are the most recurrent themes. Finally, two themes that remain open for further research are detected: the lack of structured organization during the ramp-up phase and knowledge transfer between different launches of the same product in different places.
In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set.
In order to address the reliability allocation problem of the series system, a comprehensive reliability allocation method based on a transformed function of the failure mode and effects analysis is introduced. First, considering multiple factors that affect the reliability allocation, an allocation matrix is established by employing significance factors. Subsequently, to overcome the limitations of the conventional failure mode and effects analysis–based allocation method, non-linear transform laws of failure severity and occurrence, known as transformed functions, are established. The reliability allocation results could be adjusted appropriately by choosing transform coefficients according to the desired allocation results of the system. Then, the transformed failure mode and effects analysis and the comprehensive allocation matrix are combined to give an allocation vector. Finally, a computerized numerical controlled lathe and a spindle system are used as examples. The allocation results of the transformed method, the conventional failure mode and effects analysis method and those in the correlated references are compared to emphasize the significance of the proposed allocation method in engineering practice.
A balance approach is presented to solve one-dimensional multiple stock size cutting stock problem with setup cost. The approach first utilizes a sequential pattern generation algorithm to generate a series of cutting plans based on each stock size, respectively. Then, a measure standard of cost balance utilization is used to select a current optimized cutting pattern from a cutting plan corresponding to each stock size. All item demands are dealt by the previous two steps to obtain many optimized cutting plans, and an ideal cutting plan is extracted according to the minimum sum of stock and setup costs at last. The approach is applied to two tests, and the computational results demonstrate that it possesses good cost adaptability and optimization performance.
Due to inherent properties of Ti-6Al-4V alloy, it is being used in the application of fuel injector nozzle for diesel engine, aerospace and marine industries. Since the electrochemical micromachining process involves the no heat-affected zone, no tool wear, stress- and burr-free process compared to other micromachining processes, it is widely used in the manufacturing field to fabricate complex shape and die. Hence, it is highly important to compute the optimum input parameters for enhancing the machining characteristics in such machining process. In this study, an attempt has been made to find the influence of the process parameters and optimize the parameters on machining α–β titanium alloy using Taguchi-grey relational analysis. Since applied voltage, micro-tool feed rate, electrolyte concentration and duty cycle have vital role in the process, these parameters have been chosen as the input parameters to evaluate the performance measures such as material removal rate, surface roughness and overcut in this study. From the experimental results, it has been found that micro-tool feed rate has more influence due to its importance in maintaining inter electrode gap to avoid micro-spark generation. It has also been found that lower electrolyte concentration with lower duty cycle produces lower surface roughness with better circularity on machining α–β titanium alloy. The optimum combination has been found using Taguchi-grey relational analysis and verified from confirmation test. It has also been inferred that the multi-response characteristics such as material removal rate, surface roughness and overcut can be effectively improved through the grey relational analysis.
A comprehensive numerical model is introduced in this article for estimating the tool wear based on finite element model and inverse heat conduction techniques considering the interactive and direct effects of the experimental factors of recast layer thickness, anode energy fraction and plasma flushing efficiency. The individual and interactive effects of the major thermo-physical and electro-physical parameters have been modeled to improve the introduced tool wear estimation procedure. Comparison of the numerical results with the experimental observations indicated that the developed finite element model and inverse heat conduction process was capable of predicting the tool wear with high accuracy. Additionally, application of analysis of variance technique showed that the introduced mathematical models for estimating anode energy fraction, plasma flushing efficiency and recast layer thickness are statistically significant and adequate which means that the proposed equations can be used for a variety of physical, electrical and thermal variables’ combinations.
As a new technology of reducing thickness of an aircraft skin, the mirror-milling system is widely used. The objective of this study is to optimize the support location in mirror-milling of aircraft skins. The study analyzes the machining mechanisms of mirror-milling system and establishes a theoretical model to predict the milling forces. In addition, it develops a finite element model to simulate workpiece deformation so as to predict workpiece profiles in mirror-milling system. The results of the study show that with the optimized support location, the profile error of the workpiece is reduced by 73.5%, whereas machining efficiency is increased.
The tool–workpiece interactions when a single-point diamond cutting tool with specific tool edge geometry is made to contact with a copper workpiece are evaluated by the molecular dynamics simulations under different temperatures, boundary conditions and model sizes for ultra-precision microcutting and in-process surface form measurement based on a force sensor–integrated fast tool servo. It is confirmed that the proposed multi-relaxation time method is effective to stabilize the workpiece molecular dynamics model over a wide temperature range up to the room temperature under which a practical microcutting and on-machine surface form metrology process are conducted. The boundary condition and model size of the molecular dynamics model are then optimized to make reliable and cost-effective simulations for evaluation of the elastic–plastic transition contact depth and the corresponding contact force when a diamond tool with a practical edge sharpness of up to 30 nm is employed for microcutting and on-machine surface form metrology.
The machined surface integrity of blades is of utmost importance in the power equipment manufacturing industry. Recently, many blade accidents have been attributable to the misuse of cutting fluids that were necessary in the actual machining of difficult-to-cut materials, but the effect of the cutting fluid on surface integrity and service performance has been persistently neglected. In this article, an investigation into the effect of cutting fluids on the surface quality of a typical blade material was undertaken, combined with properties of two universal cutting fluids. Element composition, surface morphology, residual stress and hardness of the machined surfaces were investigated. The results indicated that cutting fluids could not reduce cutting forces in precision machining. There were some places where local and irregular elemental Cr loss was incurred when machined with the additive Cl, and the depth of Cr loss was 1–2 µm. The machined surface under CF-206 was smooth, and the roughness of CF-210 was the highest. The tensile residual stresses of dry cutting were the highest, whereas those of CF-210 were the lowest. Surface work hardening under cutting fluids was higher, with depths of 20–30 µm. These results are significant for the control of precision machined surfaces and subsurfaces of blades with high integrity and service performance.
Measurement and quality control of turbine blades is critical to the successful operation of power plants. It has a key role in manufacturing and reverse engineering. Novel technologies continue to be developed to measure parts with complex geometries, such as turbine blades. Digitizing techniques, using both contact and noncontact methods, are used. Selecting the most appropriate digitizing method for a turbine blade requires consideration of the measuring performance of the alternative methods, including criteria such as accuracy, speed and cost. This study seeks to evaluate the practical accuracy and efficiency of various contact and noncontact digitizing methods through measurement and associated quality control of a complex part, that is, a turbine blade airfoil. Four popular technologies, using distinct underlying measurement methods, were chosen to measure a Frame 5 gas turbine blade, namely, a touch trigger probe mounted on a Zeiss coordinate measuring machine, a touch scanning probe and a spot laser probe separately mounted on Renishaw coordinate measuring machine and a linear laser system from ZScanner. The measured point cloud resulting from each method was then used to reconstruct three-dimensional computer-aided design models of the blade. The accuracy of each measuring system was evaluated against the original blade. The evaluation incorporated a comparative study of design parameters derived from the point cloud and reconstructed surfaces associated with each measurement method. The maximum error of point clouds were –123, 2530 and 2173 µm for the ZScanner linear laser, Renishaw spot laser and Renishaw touch scan, respectively. These measured errors indicated higher accuracy from linear laser method than spot laser scanning and touch scanning methods. Furthermore, the achieved standard deviations of 42, 170 and 269 µm for point clouds of ZScanner linear laser, Renishaw spot laser and Renishaw touch scan, respectively, showed that the manufacturer reported that information cannot be always reliable.
Due to the reliable feedrate fluctuation and computation load of the existing parametric curve interpolation, a fast interpolation method by cubic B-spline for parametric curve is presented which results in a minimum feedrate fluctuation and light computation load. As there are many geometry implementation tools and many good properties in the B-spline compared with the polynomial, the relation between the arc length s and curve parameter u can be fitted by the cubic B-spline accurately. Because the feedrate fluctuation of the generally used Taylor approximation method is sensitive to the curvature of the toolpath, its accuracy cannot be controlled. For a given feedrate fluctuation of 0.05%, the proposed interpolation method can guarantee the error requirements by increasing the number of the control points. After the de Boor method is applied in real time, the computation load of the cubic B-spline interpolation is decreased compared with the Taylor approximation method and higher order polynomial-fitting method. In order to save the memory consumption for storing the parameters of the fitted cubic B-spline, an iterative optimization process is applied to obtain the knot vector elements and optimize the control points. Simulations and experiments show that the interpolation method can attain high accuracy and computation efficiency. According to the simulations, for most of the complex curves, the feedrate fluctuation of the proposed interpolation method is decreased by about 50% when the feedrate is scheduled and the computation load of the proposed method is decreased by about 70% compared with the second-order interpolation method.
Strain monitoring is very important in the manufacturing, assembling, installation and servicing processes in both mechanical and civil engineering fields. Two-dimensional digital image correlation is a simple, efficient strain monitoring method, but one major bottleneck is the unacceptable error due to the unavoidable out-of-plane motions of the object in practice. We propose a "self-correction" method: employing the originally extracted strain values in different directions to correct the errors due to out-of-plane motions. It is applicable to many engineering applications with known relationship of strains in different directions. A uniaxial tension test was conducted to demonstrate the effectiveness and practicality of this self-correction method. Compared with other correction methods, this method is not only simpler but also more efficient in correcting errors due to the lens distortion caused by self-heating. Both the experiment and theoretical analyses demonstrate that this self-correction method maintains the high accuracy of the digital image correlation method.
The purpose of this study is to minimize pocketing time by exploiting the most beneficial aspects of tool dynamics and the most beneficial chronology of tool passes in contour-parallel toolpath. This is achieved by always prescribing limiting axial and radial depth pairs on a contour-parallel toolpath as a means of minimizing pocketing time within milling machine load specifications. The optimization approach is identified to be of two types: boundary to centre (b->c) execution and centre to boundary (c->b) execution. Expression for pocketing time is developed for each type taking into account the revelation that the lengths of the bivariately optimized cyclic passes between the first and last cycles constitute an arithmetic series. The presented expressions are demonstrated to be useful in systematic determination of choice of progression (either (b->c) execution or (c->b) execution) of contour-parallel pocketing operation and choice of limiting axial and radial depth pairs that guarantee minimum machining time. For example, the studied experimentally characterized case gave that (c->b) execution is more time saving than (b->c) execution by about 3.5565%–15.7690%. This experimentally characterized case also confirms the expectation that continuous tool–workpiece contact of contour-parallel toolpath always ensures a shorter pocketing time than both one-way up- and down-milling toolpaths. It is further seen that it is faster pocketing at high radial depth range of 60%–100% of tool diameter which fortunately is the range of less load restrictions. The benefits of contour-parallel toolpath relative to one-way up- and down-milling toolpaths got more strongly confirmed when the pocket got larger (for example, the time saving of (c->b) execution relative to one-way up-milling attained 51.6733% for a larger pocket, while time saving of 41.3385% was recorded for smaller pocket) and when the slope of limiting radial depth versus axial depth got less.
Electrochemical honing of gears is a productive, high-accuracy, micro-finishing and long tool life gear finishing process in which material is removed by combined action of electrolytic dissolution and mechanical scrubbing action. The use of ultrasonic-assisted electrochemical honing of gears is first proposed, and it may help to enhance the process performances of the classical electrochemical honing process by scrubbing the complete surface of the gear tooth. In this technique, the honing gear is attached on the ultrasonic vibrator to provide the ultrasonic vibrations on the workpiece surface. The focus is on an optimization of the process parameters of ultrasonic-assisted electrochemical honing of bevel gear made of AISI 1040 carbon steel. The result of experiments reveals that the applied high ultrasonic frequency (kHz) on the workpiece has the maximum influence on the process performance. The maximum percentage improvement in average and maximum surface roughness using ultrasonic-assisted electrochemical honing of bevel gear is 91.04 and 71.98, respectively. The results confirm that the ultrasonic-assisted electrochemical honing can produce a better tooth surface roughness than the electrochemical honing. This will improve bevel gear efficiency and reliability in operation.
A finite element model has been developed to determine the effectiveness of a cold compression technique to reduce the large residual stresses generated from quenching solution heat treated T-section components of aluminium alloy AA7050. To compress long components, a multi-step process is required with some amount of overlap. A parametric study has been performed to determine the effect of the compression ratio, friction coefficient, length of overlap and length of the T-section component on the residual stress distribution post-quenching and after subsequent cold compression. Generally, a percentage reduction in the peak residual stress of over 90% was found. The optimal parameters for residual stress relief by cold compression have been suggested from the cases considered.
AA2014/carbonized eggshells/SiC hybrid green metal matrix composites are fabricated by electromagnetic stir casting process at optimum parameters (squeeze pressure of 60 MPa, stirring current of 12 A, stirring time of 180 s and matrix pouring temperature of 700 °C, respectively). In the range of reinforcement parameters, the result shows that the tensile strength of hybrid metal matrix composite increases with the increase in carbonized eggshell and SiC preheat temperature. Whereas the tensile strength of AA2014/carbonized eggshell/SiC hybrid green metal matrix composite decreases with the addition of SiC beyond 2.5 wt%. The tensile strength of AA2014/carbonized eggshell/SiC hybrid green metal matrix composite increases with the increase in the eggshell weight percent until it reaches the center value (7.5 wt%); the tensile strength then starts to decrease with the increase in eggshell weight percent beyond the center limit (7.5 wt%). The optimum values of weight percent of carbonized eggshell, preheat temperature of carbonized eggshell, preheat temperature of SiC and SiC weight percent were found to be 7.5%, 300 °C, 500 °C and 2.5%, respectively, to get the maximum tensile strength (predicted: 259.12 MPa). The results reveal that sample of AA2014/7.5% eggshell/2.5% SiC shows best result among all the selected samples. The microstructure presents that the reinforcements (7.5 wt% carbonized eggshell and 2.5 wt% SiC particles) are uniformly distributed in the matrix AA2014 alloy. Transmission electron microscopy image shows proper wettability between AA2014 alloy and reinforcements (7.5 wt% carbonized eggshell and 2.5 wt% SiC particles). Density, X-ray diffraction, cost estimation, hardness, toughness, ductility and fatigue strength were also calculated to see the effect of carbonized eggshell and SiC addition in matrix alloy AA2014.
Bone drilling is one of the steps in a typical surgical operation that is performed around the world for reconstruction and repair of the fractured bone. During the last decade, various techniques, such as two-step drilling, ultrasonic-assisted bone drilling and laser drilling, have been introduced to control the level of forces and torque during bone drilling. In this research, rotary ultrasonic bone drilling has been successfully attempted to minimize the forces and torque during bone drilling. The drilling experiments were planned and carried out on pig bones using the design of experiments (response surface methodology). Analysis of variance was carried out to find the effect of process factors such as rotational speed, feed rate, drill diameter and ultrasonic vibrational amplitude on the force and torque. Statistical models were developed for the force and torque with 95% confidential interval, and confirmation experiments have been carried out to validate the models. Microcracks developed during drilling process were characterized by scanning electron microscopy. The results revealed that rotary ultrasonic bone drilling process offered a lower force and torque making it a potential process for bone drilling in orthopedic surgery.
Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition method. The aim of this work is to design and develop tungsten inert gas plus wire–based shaped metal deposition system to be used for fabricating different components directly from computer-aided design data with minimum time consumed in programming and less boring task compared to conventional robotic systems. So, this article covers the important design steps from computer-aided design data to the final deposited part. The developed additive system is capable of producing near-net-shaped components of sizes not exceeding 400 mm in three-dimensional directly from computer-aided design drawing. The results showed that the developed system succeeded to produce near-net-shaped parts for various features of SS308LSi components. Additionally, workshop tests have been conducted in order to verify the capability and reliability of the developed additive manufacturing system. The developed system is also capable of reducing the buy-to-fly ratio from 5 to 2 by reducing waste material from 1717 to 268 g for the sample components.
Titanium alloy, Ti6Al4V, is an exceptional material with several desirable properties, namely, high specific strength, high corrosion and heat resistance, which make it a promising contender in number of demanding applications. However, it has poor machinability, resulting from low thermal conductivity, high chemical reactivity with tool and spring effect during cutting. These properties lead to reduced tool life during machining, due to which its usage is limited despite excellent mechanical properties. Therefore, optimization of process parameters using response surface methodology in face milling of Ti6Al4V alloy with uncoated carbide tools has been investigated experimentally in this work. This article is focused on developing mathematical relation between input factors and response parameters, namely, surface roughness (Ra), tool wear (Tw) and tool vibration (Tv). The machining parameters are optimized for minimum Ra, Tw and Tv values. The optimal parameters are validated experimentally which showed a good agreement with the predicted results. The feed rate was found to be the most influential parameter affecting Ra and Tv, whereas cutting speed is the most effective in influencing Tw.
Liaison graph is a necessary prerequisite of assembly sequence planning for mechanical products. Traditionally, it is generated via shape matching of joints among parts, but this strategy is invalid to truss structures because they lack patterns for shape matching. In this context, this article presents an intelligent method based on support vector machine to obtain liaison graphs of truss products automatically. This method defined three kinds of oriented bounding boxes to embody the relationships of the joints in truss structures. Based on them, a series of factors are deduced as training data for support vector machine. Furthermore, two algorithms are introduced to calculate oriented bounding boxes to facilitate the data extraction. By these processes, this method established the knowledge of joints and realized the intelligent construction of liaison graph without shape matching reasoning. To verify the effect of the method, an experimental implementation is presented. The results suggest that the proposed method could recognize most joint types and construct liaison graph automatically with sufficient sample training. The correct recognition rate is more than 85%. Comparing with back-propagation neural network, support vector machine is more accurate and stable in this case. As an alternative method, it could help the engineers to arrange the assembly plan for truss structures and other similar assemblies.
The manufacturing industry is increasingly accountable for the environmental impact resulting from its activities. Research indicates that specific production processes within manufacturing plants generate significant environmental impact through energy consumption. To understand the consumption of energy in a production environment, it is necessary to outline the energy flow within the facility, along with the classification of energy usage and its relationship to processes and production outputs. It is also important to identify auxiliary (non-value added) energy within production as the area with the greatest potential for savings through changes in operational behaviour. This article introduces a practical process mapping methodology that combines energy management with value stream mapping. The methodology is based on ‘Lean’ manufacturing principles and on application to a couple of industry use cases has been shown to successfully illustrate the relationship between the energy usage and production activities for a particular value stream. Furthermore, the significant energy users in relation to the actual production process steps have been identified, and energy reduction opportunities of 42% and 50% have been quantified.
Preparation of grinding wheels is the most important effective factor in glass machining. This article presents the comparison of the iron- and copper-based grinding tools. The performance of the tools is investigated based on technical and commercial aspects using same cutting speeds, feeds, and sizes of diamond grits. Scanning electron microscope is used in order to observe the microstructures of cutting tools. The service life of the grinding tools is determined on the production line in a flat glass plant. A lifetime of Fe-based diamond tools is longer compared to the copper-based wheels. The impact of metal bond materials on the service life is examined. The results show that the Fe-based tools are more economical and more useful for grinding of glass. The holding of Fe-based bonding to diamond grit is stronger than the copper-based ones.
Metallic lattice structures manufactured using selective laser melting are widely used in fields such as aerospace and automobile industries in order to save material and reduce energy consumption. An essential element of metallic lattice structures design is determining their mechanical behaviors under loading conditions. Theoretical method based on beam theory has been proposed for evaluating the behaviors of the commonly used body-centered cubic lattice structures. However, it is difficult to predict theoretically the properties of the uniaxially reinforced lattice structures based on the body-centered cubic structures. Since the reinforced structures have superior strength to weight ratio and are deemed promising in lightweight-design applications, this article proposed a force-method-based theoretical method to calculate the mechanical properties of the body-centered cubic structure and its two types of uniaxially reinforced structures fabricated via selective laser melting. The finite element analysis and compression experiment study of selective laser melting samples made using Ti6Al4V powders demonstrated the validity of the proposed analytical method.
Dead metal cap plays an important role in the microcutting process because target material piled up on the tool–chip–workpiece interface can alter the cutting geometry. The target of this study is to model and simulate the micro-orthogonal cutting process in the presence of dead metal cap in order to investigate the effects of this phenomenon on the micromachining process outputs (cutting force, thrust force and chip thickness) and stress distribution, equivalent plastic strain and temperature inside the workpiece shear zones. For this purpose, the finite element method with explicit dynamic solution and adiabatic heating effect along with arbitrary Lagrangian–Eulerian approach is used. It is shown that the finite element models with current state-of-the-art assumptions cannot take into account the dead metal cap by default. For this reason, dead metal cap is artificially introduced on the rounded tool edge in this study for carrying out a proper analysis. Several simulations with different dead metal cap geometries are performed and obtained results show that prediction of cutting force, thrust force and chip thickness are sensitive to the presence of dead metal cap and its geometry. Micro-orthogonal cutting experiments are carried out on tubular AISI 1045 workpieces for validating and interpreting simulated results. The error between predicted and experimental data is calculated, and it is shown that simulation performances can be improved by considering the dead metal cap into the process model. For example, it is possible to reduce the error to less than 5% in case of thrust force prediction. This study points out how the target material’s Von Mises stress, equivalent plastic strain and temperature distribution are sensitive to any alteration of the edge geometry due to the dead metal cap. The best dead metal cap configuration in terms of agreement with experiments is also the one introducing a more homogeneous distribution of these quantities along the shear plane.
In this article, a modification of multi-objective differential evolution based on simulated annealing is proposed to solve a general tri-objective non-permutation flow shop problem. The flow shop system considers the release dates, machine breakdowns, past-sequence-dependent setup times and learning effect for all the jobs. The algorithm proposed to tackle such a model combines the robustness of differential evolution with the rapid convergence and conditional diversification of simulated annealing. For small and medium low-sized problems, the solutions found by the proposed algorithm are compared with the exact solutions, achieved by augmented -constraint method. Due to the high complexity of the model, for medium high and large-sized problems, the algorithm is tested against the imperialist competitive algorithm and the multi-objective differential evolution scheduling. Comparisons of the results show a good balance between intensification and diversification in the proposed algorithm.
The ultra-precision spindle is the key component of ultra-precision machine tool, which largely influences the machining accuracy. Its frequency characteristics mainly affect the frequency domain error of the machined surface. In this article, the error measurement setup for the ultra-precision aerostatic spindle in a flycutting machine tool is established. The dynamic and multi-direction errors of the spindle are real-time measured under different rotation speeds. Then, frequency domain analysis is carried out to obtain its regularity characteristics based on the measurement result. Through the analysis, the main synchronous and asynchronous errors with relatively large amplitude of the spindle errors are found, and the amplitude change law of these main spindle errors is obtained. Besides, the cause of the main synchronous and asynchronous errors is also analyzed and indicated. This study deepens the understanding of ultra-precision spindle dynamic characteristics and plays the important role in the spindle frequency domain errors’ control, machining process planning, frequency characteristics analysis and oriented control of the machined surface errors.
Numerous hard, brittle metals have been shown to form segmented chips during machining operations, which has been shown to be linked to high vibration levels in turning and milling processes. This article concerns quantitative comprehension of segmentation-driven vibration in end-milling process. First, dynamic model of milling process with impact of segmented chip is presented, and a periodic cutting force model related with segmented chip is proposed. Second, for experimental observation, a series of tests are carried out concerning modal test of cutting system; chip morphology, tool vibration during cutting, surface location error, and high-frequency sampling measurements of cutting force signal are realized. The method used for calculating the frequency of segmentation chip by oblique cutting is deduced. It is found that at low feed rate, the periodic cutting force is affected by the natural frequency of cutting system, segmentation chip, and tool vibration. Finally, amplitude–frequency response for quasi-single degree of freedom is employed to elaborate the relationship between segmentation frequency and natural modes of system. The results show that when the ratio (frequency of segmented chip to natural frequency of system) is a noninteger value or above 3, no significant vibrations of cutting system are observed in milling titanium alloy Ti6Al4V.
Quality function deployment is a cross-functional decision-making tool that converts customer needs into technical attributes of new products. Fuzzy numbers are usually adopted to evaluate the customer need importance and the customer need–technical attribute relationships. However, the weighted normalized customer need–technical attribute relationship matrix is not always full rank. If the different fuzzy numbers of two technical attributes are defined as the fuzzy negative ideal solutions, both the closeness coefficients are 0, and the traditional technique for order preference by similarity to an ideal solution cannot prioritize the two technical attributes. Actually, the rankings of different fuzzy numbers are not identical. To solve this problem, we present a new technique for order preference by similarity to an ideal solution to prioritize technical attributes in the fuzzy quality function deployment. The fuzzy positive ideal solution, fuzzy negative ideal solution, and distance measurement of the new technique for order preference by similarity to an ideal solution are improved. As a result, the proposed method not only prioritizes various forms of numbers without considering the lower and upper limits, the median, and boundary interval but also deals with the nonfull rank matrix. Besides, the Theory of Inventive Problem Solving is used to solve technical conflicts which are identified by the line-fitting method. The prioritization results from the proposed method can help to reasonably allocate design and manufacturing resources. Finally, a case on phone shell is given to illustrate the application of the proposed quality function deployment method.
Electrical discharge turning is a unique form of electrical discharge machining process, which is being especially developed to generate cylindrical forms and helical profiles on the difficult-to-machine materials at both macro and micro levels. A precise submerged rotating spindle as a work holding system was designed and added to a conventional electrical discharge machine to rotate the workpiece. A conductive preshaped strip of copper as a forming tool is fed (reciprocate) continuously against the rotating workpiece; thus, mirror image of the tool is formed on the circumference of the workpiece. The machining performance of electrical discharge turning process is defined and influenced by its machining parameters, which directly affects the quality of the machined component. This study presents an investigation on the effects of the machining parameters, namely, pulse-on time, peak current, gap voltage, spindle speed and flushing pressure, on the material removal rate (MRR) and surface roughness (Ra) in electrical discharge turning of titanium alloy Ti-6Al-4V. This has been done by means of Taguchi’s design of experiment technique. Analysis of variance as well as regression analysis is performed on the experimental data. The signal-to-noise ratio analysis is employed to find the optimal condition. The experimental results indicate that peak current, gap voltage and pulse-on time are the most significant influencing parameters that contribute more than 90% to material removal rate. In the context of Ra, peak current and pulse-on time come up with more than 82% of contribution. Finally, the obtained predicted optimal results were verified experimentally. It was shown that the error values are all less than 6%, confirming the feasibility and effectiveness of the adopted approach.
A cutting force model, based on a predictive model for orthogonal cutting, is developed for force predictions in end milling of titanium alloy Ti6Al4V. The model assumes a semi-stationary process for the serrated chip formation. The Johnson–Cook material model that couples strain hardening, strain rate sensitivity and thermal softening effects is applied to represent the material strength. A thermal model considering the tool thermal properties is integrated to account for the high temperature rise due to the low thermal conductivity of Ti6Al4V. To extend the predictive model to milling, the end mill is discretised into several axial slices, and an equivalent cutting edge is used to include the end cutting edge effect caused by the first axial slice. The model is assessed by comparing its prediction with the experimental results and a mechanistic model for verification. The results show that the proposed model outperforms the mechanistic model with higher accuracy in force prediction.
Powder-bed electron beam additive manufacturing has the potential to be a cost-effective alternative in producing complex-shaped, custom-designed metal parts using various alloys. Material thermal properties have a rather sophisticated effect on the thermal characteristics such as the melt pool geometry in fabrications, impacting the build part quality. The objective of this study is to achieve a quantitative relationship that can correlate the material thermal properties and the melt pool geometric characteristics in the electron beam additive manufacturing process. The motivation is to understand the interactions of material property effect since testing individual properties is insufficient because of the change of almost all thermal properties when switching from one to the other material. In this research, a full-factorial simulation experiment was conducted to include a wide range of the thermal properties and their combinations. A developed finite element thermal model was applied to perform electron beam additive manufacturing process thermal simulations incorporating tested thermal properties. The analysis of variance method was utilized to evaluate different thermal property effects on the simulated melt pool geometry. The major results are summarized as follows. (1) The material melting point is the most dominant factor to the melt pool size. (2) The role of the material thermal conductivity may outweigh the melting point and strongly affects the melt pool size, if the thermal conductivity is very high. (3) Regression equations to correlate the material properties and the melt pool dimension and shape have been established, and the regression-predicted results show a reasonable agreement with the simulation results for tested real-world materials. However, errors still exist for materials with a small melt pool such as copper.
High-speed milling, which provides an efficient approach for high-quality machining, is widely adopted for machining difficult-to-machine materials such as Inconel 718. For high-speed milling of Inconel 718 curved surface parts, the spindle speed which determines cutting speed directly is regarded as an important cutting parameter related to tool wear and machining efficiency. Meanwhile, because of the changing geometric features of curved surface, cutting force is changing all the time with the variation of geometric features, which influences not only tool wear but also machining quality significantly. In this study, the influence of spindle speed on coated tool wear in high-speed milling of Inconel 718 curved surface parts is studied through a series of experiments on considering tool life, cutting force, cutting force fluctuation, and machining efficiency. According to the experimental results, the appropriate spindle speed that can balance both the tool life and the machining efficiency is selected as 10,000 r/min for high-speed milling of Inconel 718 curved surface parts. In addition, the coated tool wear mechanism is investigated through scanning electron microscopy–energy dispersive x-ray spectroscopy analysis. The results show that at the beginning wear stage and the stable wear stage, the coated tool wear is mainly caused by mechanical wear. Then, with the increasing cutting temperature due to the blunt tool edge, the tool wear becomes compound wear which contains more than one wear form so as to cause a severe tool wear.
Several methods and tools have been developed to facilitate sustainable product design, but they lack critical application of the ecological design (eco-design) process and economic costing, particularly during the conceptual design phase. This research study overcomes these deficiencies by integrating eco-design approaches across all phases of the product life cycle. It proposes an eco-design case-based reasoning tool that is integrated with the recently developed ecological quality function deployment method, which supports sustainable product design. The eco-design case-based reasoning tool is an intuitive decision-support tool that complements the ecological quality function deployment method and proposes solutions related to customers’ requirements and the environmental and economic impacts of the product. The ecological quality function deployment method ensures that customers’ needs are considered within the context of product sustainability. The novelty of this article is in the development of the eco-design case-based reasoning tool which is based on the premise that if experiences from the ecological quality function deployment process can be captured in some useful form, designers can refer to and learn from them. This approach helps industrial decision-makers propose solutions by reusing solutions from similar cases and from their past experiences. The novelty is in the way the cases are structured and new cases are generated, using life-cycle assessments, cost estimations, and information about related manufacturing processes and means of transportation. This article demonstrates the applicability of the proposed approach through an industrial case study.
Manufacturing and, in particular, machining are responsible for a significant portion of global industrial energy consumption (25%). Previous research has shown that precise selection of cutting parameters can improve the energy consumption of machining processes. Cryogenic machining has attracted significant attention for improving the machinability of difficult-to-machine materials while also eliminating the environmental and health issues associated with the use of cutting fluids. Despite the advantages, there is a considerable research gap in cryogenic milling operations. This article investigates the effect of cryogenic cooling using liquid nitrogen in end milling of Ti-6Al-4V. A robust and rigorous methodology was developed and a series of machining experiments were conducted using a combination of cutting parameters repeated at dry, flood and cryogenic cooling environments. The investigations indicated that cryogenic cooling considerably reduce tool wear when compared to dry and flood cooling while allowing for using higher cutting speeds. The cutting tool used for cryogenic machining at 200 m/min cutting speed, 0.03 mm/tooth feed rate and 5 mm depth of cut showed minimum flank wear. Furthermore, the investigations demonstrated that using the machine’s coolant pump in flood cooling resulted in higher power and energy consumption than dry and cryogenic cooling. This article clearly shows that higher material removal rates are required in order to minimise specific machining energy. Therefore, since cutting speed is limited in dry machining, cryogenic machining is the most favourable as higher cutting speeds can be used. Using cryogenic machining at 200 m/min cutting speed resulted in an 88% reduction in energy consumption of the machine tool as compared to flood cooling at 30 m/min while minimum tool wear (10 µm) was detected. This clearly demonstrates the significant capabilities of cryogenic machining when compared with more conventional machining approaches.
This article presents an investigation of the machining response of metallurgically and mechanically modified materials at the micro-scale. Tests were conducted that involved micro-milling slots in coarse-grained Cu99.9E with an average grain size of 30 µm and ultrafine-grained Cu99.9E with an average grain size of 200 nm, produced by equal channel angular pressing. A new method based on atomic force microscope measurements is proposed for assessing the effects of material homogeneity changes on the minimum chip thickness required for a robust micro-cutting process with a minimum surface roughness. The investigation has shown that by refining the material microstructure the minimum chip thickness can be reduced and a high surface finish can be obtained. Also, it was concluded that material homogeneity improvements lead to a reduction in surface roughness and surface defects in micro-cutting.
Hydraulic pump degradation feature extraction is a key step of condition-based maintenance. In this article, a novel method based on local characteristic-scale decomposition (LCD) and discrete cosine transform–composite spectrum (DCS) fusion algorithm is proposed. In order to reduce noises and other disturbances, vibration signals are first processed by LCD with the high frequency harmonic. Detail components with sensitive information are achieved by the selection of intrinsic scale components. Furthermore, on the basis of the earlier composite spectrum (CS), the DCS fusion algorithm is proposed to make fusion of the obtained detail components for improving the feature performance. The DCS entropy is extracted as the fault degradation feature. Analysis of the hydraulic pump degradation experiment demonstrates that the proposed algorithm is feasible and effective to indicate the performance degradation of the hydraulic pump.
The selection of optimal welding parameters in any welding process significantly improves the quality, production rate, and cost of a component. The weld bead characteristics such as bead width, depth of penetration, and heat-affected zone are the prominent factors for evaluating the performance of a welded joint. The work presents a novel evolutionary multi-objective optimization approach to derive the optimal laser welding conditions for the weld bead geometrical parameters. The welding experiments were conducted with the consideration of pulse frequency, pulse width, welding speed, and pulse energy as the process-control variables to evaluate the weld bead characteristics. Empirical models for the bead characteristics were developed in terms of the input variables using response surface methodology. The individual and interactive effects of the variables on the responses were also analyzed. As the influence of control variables on the bead characteristics is conflicting in nature, the problem is formulated as a multi-objective optimization problem to simultaneously optimize the output parameters. The aim is to simultaneously minimize the bead width, maximize the depth of penetration, and minimize the heat-affected zone. An efficient evolutionary algorithm called non-dominated sorting genetic algorithm-II was applied to derive the set of Pareto-optimal solutions. The derived optimal process responses were confirmed with the experimental values. The proposed integrated methodology can be applied to any welding process to automate the process conditions in computer-integrated manufacturing environment.
A novel double-crowned tooth geometry is proposed by the application of ease-off topography for spiroid gear manufactured by precision casting process, with the goals of localizing the bearing contact and obtaining a perfect function of transmission errors. The modified tooth surface is applied as the reference geometry to machine the die cavity geometry that will produce such geometry of the gears. The tooth geometry of crowned gear was achieved first from a pre-designed controllable function of transmission errors along the desired contact path. Then, the desired ease-off topography along the contact line is designed and calculated computationally from the given mathematic model of surface modification. The geometry of double-crowned spiroid gear could be reconstructed by superimposing the ease off of contact line direction on the profile-crowned tooth surface. The article provides numerical examples to validate the feasibility of ease-off modification methodology that was used to produce the double-crowned tooth geometry for the gears, while tooth contact analysis is performed computationally to investigate the stability of bearing contact and function of transmission errors to alignment.
This article deals with the lean strategy evaluation process using SWOT (strengths, weaknesses, opportunities and threats) analysis aimed at identifying lean strategies and providing an initial decision framework. It involves specifying the objective of the industry and identification of internal and external factors and its sub-factors and lean strategies, which are either favourable or unfavourable in the accomplishment of the stated objective. However, the SWOT analysis method does not provide an analytical method to evaluate the priorities of identified decisive strategic factors. To overcome this limitation, this article presents a case study in an Indian foundry industry using two multiple criteria decision-making methods, that is, analytic network process and modified TOPSIS (technique for order of preference by similarity to ideal solution), to provide a computable basis in determining the rank of lean strategies. In this approach, the analytic network process is used to calculate the priorities of identified SWOT factors and sub-factors and the modified TOPSIS is applied to rank the lean strategies. A sensitivity analysis is also provided to illustrate how ‘sensitive’ the proposed model is to changes in the priorities of SWOT factors. The results show that the quantitative SWOT analysis–based approach is a feasible and exceedingly capable method that provides vital sensitivity in evaluating the priorities of lean strategies for an Indian foundry industry and can also be employed as an effective method for many other complex decision-making processes.
Error compensation technique is a recognized and cost-effective method to improve machining accuracy of machine tools. In this article, a new compensation method for geometric error is proposed based on Floyd algorithm and product of exponential screw theory. Based on topological structure and measured data, volumetric geometric error modeling is established by product of exponential screw theory. Then, the improved Floyd minimum-distance method was used to establish an error compensation model by adjusting weight unceasingly. In order to verify the effectiveness and generality of the method proposed in this article, two experiments were designed. A total of 5 five-axis machining centers of the same type with different use time were selected to carry out the simulation experiments. Results show that the Floyd method can provide higher compensation precision, that is, Floyd algorithm compensation method can keep positioning errors within the range [–8 µm, 9 µm]. In addition, roundness error, coaxial error, and surface roughness were reduced in the actual machining experiments of two machined conical tables. Therefore, it can be seen that the proposed compensation method is effective to improve machining accuracy of machine tools.
Higher tool wear and inferior surface quality of the specimens during machining restrict metal matrix composites’ application in many areas in spite of their excellent properties. The researches in this field are not well organized, and knowledge is not properly linked to give a complete overview. Thus, it is hard to implement it in practical fields. To address this issue, this article reviews tool wear and surface generation and latest developments in machining of metal matrix composites. This will provide an insight and scientific overview in this field which will facilitate the implementation of the obtained knowledge in the practical fields. It was noted that the hard reinforcements initially start abrasive wear on the cutting tool. The abrasion exposes new cutting tool surface, which initiates adhesion of matrix material to the cutting tool and thus causes adhesion wear. Built-up edges also generate at lower cutting speeds. Although different types of coating improve tool life, only diamond cutting tools show considerably longer tool life. The application of the coolants improves tool life reasonably at higher cutting speed. Pits, voids, microcracks and fractured reinforcements are common in the machined metal matrix composite surface. These are due to ploughing, indentation and dislodgement of particles from the matrix due to tool–particle interactions. Furthermore, compressive residual stress is caused by the particles’ indentation in the machined surface. At high feeds, the feed rate controls the surface roughness of the metal matrix composite; although at low feeds, it was controlled by the particle fracture or pull out. The coarser reinforced particles and lower volume fraction enhance microhardness variations beneath the machined surface.
For any large weldment with many welding seams, the welding sequence and direction have a strong influence on the assembly and service performance, especially for the side beam of the bogie frame of a high-speed rail passenger car (CHR3; CRRC, Changchun, China). Because different combinations of the welding sequence and direction greatly increase the computational time and research costs, a three-dimensional finite element approach was developed to investigate the optimal welding sequence and direction. Then, a surrogate model was established by design of experiment and used the concepts of a pointer and stack. Finally, the welding sequence and direction were optimized by the discrete particle swarm optimization algorithm. The max residual deformation and stress of the optimal result were –3.92 mm and 212.56 MPa, respectively, which is approximately 22% and 38% lower than the traditional enterprise plan, respectively. Furthermore, a weighted form of the residual deformation and stress was proposed to the end of optimum comprehensive effect, and the result also had 11% and 28% reduction, respectively. The simulation result of the optimal plans well reproduced the theoretical distribution results of the residual deformation and stress. It is proven that the optimal result can improve the welding quality and process of the side beam weldment in production.
Friction stir welding is a solid-state welding technique for joining metals such as aluminum alloys quickly and reliably. This article presents a design of experiments approach (central composite face–centered factorial design) for predicting and optimizing the process parameters of dissimilar friction stir welded AA6351–AA5083. Three weld parameters that influence weld quality were considered, namely, tool shoulder profile (flat grooved, partial impeller and full impeller), rotational speed and welding speed. Experimental results detailing the variation of the ultimate tensile strength as a function of the friction stir welding process parameters are presented and analyzed. An empirical model that relates the friction stir welding process parameters and the ultimate tensile strength was obtained by utilizing a design of experiments technique. The models developed were validated by an analysis of variance. In general, the full impeller shoulder profile displayed the best mechanical properties when compared to the other profiles. Electron backscatter diffraction maps were used to correlate the metallurgical properties of the dissimilar joints with the joint mechanical properties as obtained experimentally and subsequently modeled. The optimal friction stir welding process parameters, to maximize ultimate tensile strength, are identified and reported.
Bonnet polishing has been successfully used for ultra-precision machining of the large-aperture aspheric optics. To accomplish online monitoring of executive condition of the removing function and state of the polishing machine, key technological parameters and processing condition factors need to be acquired in real time and coupled back. A novel data fusion method which combines hardware synchronous signal and correcting algorithm based on the principle of linear extrapolation is proposed in allusion to data acquisition distortion caused by asynchronous sampling frequency and communication delay between different systems. The estimate values are obtained by dynamically correcting original acquired data, and the upper bound of the error is deduced with the speed and the acceleration of the signal. The simulation results showed that the data fusion method can significantly reduce the error of data acquisition. The experimental results confirmed that the data fusion method can be effectively applied to monitor the optics bonnet polishing process online.
Ultrasonic-assisted machining is an advanced method which allows significant improvements in processing of materials. In this study, a finite element model is developed to study the effect of ultrasonic vibration on machinability of AISI 304 stainless steel in which the results are compared with conventional cutting process. A pneumatic quick-stop device and an optical microscope are applied to validate the simulation results by measuring shear angle and sticky region experimentally. As a result, the analysis of heat generation in primary and secondary deformation zones shows that temperature increases in the primary zone when ultrasonic vibration is used, while a significant reduction in temperature is seen in the tool–chip contact zone. This area is considerably effective on the length of sticky region. Moreover, the influence of cutting speed and feed rate on tool–chip engagement time is investigated by the analysis of cutting force profile.
In recent times, nickel-based super alloys are widely utilized in aviation, processing, and marine industries owing to their supreme ability to retain the mechanical properties at elevated temperature in combination with remarkable resistance to corrosion. Some of the properties of these alloys such as low thermal conductivity, strain hardening tendency, chemical affinity, and presence of hard and abrasives phases in the microstructure render these materials very difficult-to-cut using conventional machining processes. In this work, an experimental setup was developed and integrated with the existing electrical discharge machining system for carrying out powder-mixed electrical discharge machining process for Inconel 625. The experiments were planned and conducted by varying five different variables, that is, powder concentration, peak current, pulse-on time, duty cycle, and gap voltage based on the central composite design of response surface methodology. Effects of these parameters along with powder concentration were investigated on various surface integrity aspects including surface morphology, surface roughness, surface microhardness, change in the composition of the machined surface, and residual stress. Results clearly indicated that addition of powder to dielectric has significantly improved surface integrity compared to pure dielectric. Among the powders used, silicon has resulted in highest microhardness, that is, almost 14% more than graphite. Lowest surface roughness (approximately 50% less than pure kerosene) and least residual stress were obtained using silicon powder (approximately 8% less than graphite-mixed dielectric). Relative content of nickel was reduced at the expense of Nb and Mo after addition of powders like aluminum and graphite in dielectric during electrical discharge machining.
The ultrasonic impact treatment process is widely used to improve the fatigue life of the weldments by inducing compressive residual stresses at the sub-surface. The purpose of the article is to conduct the dynamic elastic–plastic finite element analysis of multiple impacts on 5A06 aluminum alloy with different controlled parameters. The numerical model was validated by pin drop test. The changes in penetration depth, maximum compressive residual stress, and surface residual stress were obtained by analyzing the residual stress field and equivalent plastic strain. The effect of impact times, impact velocities, pin shapes, and impact angles on the residual stress was investigated so that the ultrasonic impact treatment parameters could be controlled to obtain expected residual stress distributions.
Macor ceramic has been well recognized as an eminent engineering material which possesses enlarged industrial usage owing to its excellent and versatile properties. However, its fruitful and economic processing is still unanswered. This article has targeted to experimentally investigate the influence of numerous process variables on machining characteristics in rotary ultrasonic machining of Macor ceramic. The impact of different input factors, namely, spindle speed, feed rate, coolant pressure, and ultrasonic power has been appraised on process responses of interest, that is, material removal rate and chipping size. The experimental plan was designed by employing response surface methodology through central composite rotatable design. The variance analysis test has also been performed with a view to observe the significance of considered parameters. Microstructure of machined samples has also been evaluated and analyzed using scanning electron microscope. This analysis has revealed and confirmed the presence of dominated brittle fracture that caused removal of material along with the thin plastic deformation in rotary ultrasonic machining of Macor ceramic. The reliability and competence of the developed mathematical model have been established with test results. The multi-response optimization of machining responses has also been done by utilizing desirability approach, and at optimized parametric setting, the obtained experimental values for material removal rate and chipping size are 0.4762 mm3/s and 0.3718 mm, respectively, with the combined desirability index value of 0.937.
Tool deflection induced by cutting force could result in dimensional inaccuracies or profile error in corner milling process. Error compensation has been proved to be an effective method to get accuracy component in milling process. This article presents a methodology to compensate profile errors by modifying tool path. The compensation effect strongly depends on accuracy of the cutting force model used. The mathematical expression of chip thickness is proposed based on the true track of cutting edge for corner milling process, which considers the effect of tool deflection. The deflection of tool is calculated by finite element method. Then, an off-line compensation algorithm for corner profile error is developed. Following the theoretical analysis, the effect of the error compensation algorithm is verified by experimental study. The outcome provides useful comprehension about selection of process conditions for corner milling process.
Applications of metal–ceramic composites are increasing in advanced materials field; however, efficient utilization of these materials depends on the cost involved in processing and structure–properties correlations. Processing of materials through microwave energy has already been accepted as a well-established route for many materials. In this work, composites of nickel-based metallic powder (matrix) and SiC powder (reinforcement) were successfully casted by microwave heating. The mechanism for the development of composite castings using microwaves is discussed with proper illustrations. The results of microstructure analysis of the developed cast revealed that uniform equiaxed grain growth with uniform dispersion of reinforcement. The results of X-ray diffraction analysis revealed that during microwave heating some metallurgical changes took place, which led to higher microhardness of cast. Micowave processed casting revealed lower defects (~1.75% porosity) and average Vickers microhardness of 920 ± 208 HV. This work reports the successful applications of microwaves in manufacturing, in the form of melting and casting of metallic powders.
This article describes the results of the experimental research on the heat-affected zone of the subsurface layers of eroded surface on medium-alloyed samples of steel EN X37CrMoV5-1 (W.-Nr. 1.2343) which occurs in die-sinking electrical discharge machining with Cu electrode. It assesses the direct effect and consequences of the heat-affected zone on the final quality of the machined surface. The aim of the experiments was to contribute to the knowledge database defining the influence of the main technological parameters of electrical discharge machining on the microhardness changes and the total depth of the heat-affected zone of the subsurface layers of experimental samples. The results of the experimental measurement were transformed into the mathematical models allowing simulation and prediction of the final quality of the machined surface after die-sinking electrical discharge machining tool steels with Cu electrode. The purpose of the mathematical models is to determine the optimal combination of process parameters and thereby achieve the desired quality of the products produced by this advanced technology.
Electronic systems are prone to failures, whether during manufacture or throughout their in-service lifetime. A number of design and fabrication techniques are presently employed that maintain an economical production yield. However, the cost of through-life maintenance and fault mitigation operations for complex, high-value systems remains a major challenge and requires new design methods in order to increase their resilience. In this article, the focus is on applications that are sensitive to transient random errors caused by single-event upsets and multiple-bit upsets occurring within their electronic systems and sub-systems, as well as applications that benefit from fault detection and localisation. A novel self-restoration strategy is proposed based on a two-layer design approach comprising a fault-tolerant coordination layer with convergent cellular automata and a configurable functional logic layer. This design strategy is able to self-reconstruct the correct functional logic configuration in the event of transient faults without external intervention. The necessary convergent cellular automata rule set and state table sizes for 3 x 3 and 4 x 4 binary coded patterns are analysed in order to estimate the generic resource requirements for larger designs. Additionally, the possibility of exploiting the design for built-in fault detection and diagnostic reporting is investigated.
The aim of this work is to fabricate the high-density polyethylene–copper composites by submerged friction stir processing at different traverse speeds. The scanning electron microscopy is used to analyze the distribution of microstructure and particles. The experimental results indicated that the macrostructure morphology, microstructure and tensile strength vary depending on the traverse speed. Compared with the pure high-density polyethylene, Cu-filled polymer composites showed lower tensile strength and higher microhardness. The maximal values of the tensile strength and microhardness were achieved at traverse speeds of 30 and 15 mm/min, respectively. The thermal properties of Cu-filled high-density polyethylene composites were studied by differential scanning calorimetry. The crystalline content of the composites was decreased due to the addition of copper. From the experimental tests, it can be concluded that submerged fiction stir processing has a great potential for producing polymer–metal composites.
In this study, by cutting electrical steel stator laminations, one of the most important components of electrical machines by different cutting methods, the effects of these cutting methods on motor efficiency are investigated. As cutting methods, wire electrical discharge machining, punching, laser and abrasive water jet methods are used. Burr formation at the cutting edge leads to short circuits during the steel packaging and causes magnetic losses in steel packages to increase. In addition, depending on the cutting methods, electrical steel lamination insulation layer is damaged as a result of residual and thermal stress formations. These negative conditions cause iron, friction and windage, stator, rotor and additional load losses occurred in the engine to decrease. In order to minimize these cases, electrical steel stator laminations are cut with the cutting parameters determined as a result of pre-cut tests and 5.5-kW induction motors are manufactured. These manufactured motors, according to IEC 60034-2-1-1B method, are subjected to no-load performance tests in addition to six different loading ratios of 25%–50%–75%–100%–115%–125% and constant 50 Hz frequency. As a result of the test measurements, losses occurred in electrical steels cut with abrasive water jet are found to be higher than the other cutting methods. In addition, in terms of the motor performance, the best results are obtained with wire electrical discharge machining cutting method.
Based on a well-designed growth procedure, a tri-material, namely, a three-layer boron-doped micro-crystalline, undoped micro-crystalline and undoped nano-crystalline composite diamond film, is deposited on the pretreated WC–6 wt% Co substrate, the basic characters of which are systematically studied and compared with some other commonly used diamond films. Besides, the growth times for three respective layers are accordingly determined. It is further clarified that the underlying boron-doped micro-crystalline diamond layer can well adhere to the WC–Co substrate due to either the reduction in the residual stress or the formation of B–Co compounds. There is no doubt that the surface undoped nano-crystalline diamond layer with relatively lower hardness and initial surface roughness is more convenient to be polished to the required surface roughness. Moreover, when the growth times for the middle undoped micro-crystalline diamond layer and the surface undoped nano-crystalline diamond layer are both appropriate, the undoped micro-crystalline diamond layer with extremely high diamond quality and hardness can effectively reinforce the surface hardness of the whole composite film. Based on the discussions on the influences of the growth times for the different layers on the performance of the composite diamond film, the growth times for the boron-doped micro-crystalline diamond, undoped micro-crystalline diamond and undoped nano-crystalline diamond layers are, respectively, determined as 4, 4 and 2 h. Under such conditions, the reinforcement effect of the middle layer on the surface hardness can be guaranteed, and the undoped nano-crystalline diamond grains have totally covered the undoped micro-crystalline diamond layer.
It is going to be increasingly important for manufacturing system designers to incorporate human activity data and ergonomic analysis with other performance data in digital design modelling and system monitoring. However, traditional methods of capturing human activity data are not sufficiently accurate to meet the needs of digitised data analysis; qualitative data are subject to bias and imprecision, and optically derived data are hindered by occlusions caused by structures or other people in a working environment. Therefore, to meet contemporary needs for more accurate and objective data, inertial non-optical methods of measurement appear to offer a solution. This article describes a case study conducted within the aerospace manufacturing industry, where data on the human activities involved in aircraft wing system installations was first collected via traditional ethnographic methods and found to have limited accuracy and suitability for digital modelling, but similar human activity data subsequently collected using an automatic non-optical motion capture system in a more controlled environment showed better suitability. Results demonstrate the potential benefits of applying not only the inertial non-optical method in future digital modelling and performance monitoring but also the value of continuing to include qualitative analysis for richer interpretation of important explanatory factors.
Peripheral milling process productivity or quality can be improved by controlling either cutting force or contour error. While each means for improvement is often addressed individually, efforts to control both aspects simultaneously are less common in the literature. This article describes an approach to control both the contour error and force using an adaptive robust controller. The axes dynamic behavior and tool deflection are considered as the two major sources of error expressly considered in the control design and are embedded in a global task coordinate frame representation of contour error. The adaptive control component maintains high-performance control of both force and contour error in the presence of significant model error or external disturbances. The control approach is implemented on a three-axis machine tool for validation. Experimental results indicate that significant improvements to both contour error and force regulation have been achieved.
The automotive, aerospace and energy industries have lately increased their search for materials which must have high mechanical resistance/weight ratio and capability to maintain the mechanical properties in high temperatures and at corrosive environments in order to produce critical parts of their equipment. The nickel-based alloys are one type of materials which have been a good answer for this search. On the other hand, the very good mechanical properties of these alloys make their manufacturing very difficult, especially when machining processes are used. Among other problems in the machining of these alloys, due to the high mechanical resistance in high temperature, tool lives used to be much shorter than when steel alloys are machined, forcing cutting speeds to be much lower and, consequently, to have less productive processes. The main goal of this work was to test an alternative to increase tool life in the turning of Inconel 625 nickel-based alloy by the use of high-pressure coolant. This system was tested using different directions of the fluid flow (toward the rake face, toward the flank face and directing the fluid simultaneously toward these two tool faces) compared to the conventional way of applying fluid. The results show that the use of high-pressure coolant harms the notch wear development and, consequently, increases tool life with simultaneous improvement of workpiece surface roughness in some cases. However, the application of high-pressure coolant over both flank and rake faces at the same time did not provide any improvement.
Process management is considered to be an essential approach to improve the performance of an enterprise. The process of an engineering project is considered to be a formalised workflow accompanied by a set of decisions. With decisions being made by taking account of information from various sources, the operation and management of modern engineering projects has to deal with increasing amounts of dynamic and changing project information. Understanding and interpreting this information for use in process management can generate challenges in practice. This might be caused by constraints of time and resource, the distributed structure of the information and a lack of modelled domain knowledge. To address these challenges, the research described in this paper focuses on techniques that support automation of the process management of engineering projects, from a data-driven perspective. The research includes elements of process modelling, monitoring and evaluation of such projects, through a proposed automatic process analysis system. The proposed system works with live and historical data. Within this paper, the design and implementation of the system is described. The use of techniques such as autonomic computing, data mining and KM technologies are shown, and the system functionality is demonstrated through the use of a dataset from an aerospace organisation.
Metal sheets have the ability to be formed into nonstandard sizes and sections. Displacement-controlled computer numerical control press brakes are used for three-dimensional sheet metal forming. Although the subject of vendor neutral computer-aided technologies (computer-aided design, computer-aided process planning and computer-aided manufacturing) is widely researched for machined parts, research in the field of sheet metal parts is very sparse. Blank development from three-dimensional computer-aided design model depends on the bending tools geometry and metal sheet properties. Furthermore, generation and propagation of bending errors depend on individual bend sequences. Bend sequence planning is carried out to minimize bending errors, keeping in view the available tooling geometry and the sheet material properties’ variation. Research reported in this article attempts to develop a STEP-compliant, vendor neutral design and manufacturing framework for discrete sheet metal bend parts to provide a capability of bidirectional communication between design and manufacturing cycles. Proposed framework will facilitate the use of design information downstream at the manufacturing stage in the form of bending workplan, bending workingsteps and a feedback mechanism to the upstage product designer. In order to realize this vendor neutral framework, STEP (ISO 10303), AP203, AP207, and AP219 along with STEP-NC (ISO14649) have been used to provide a basis of vendor neutral data modeling.
The study of surface texturing on a metallic surface has become a great area of interest of researchers in the last few decades. Surface texturing is employed for enhancing the performance of the surface in its working environment. As the characterization techniques have been evolving very fast, researchers have started mimicking the natural surfaces to take the advantages of their characteristics (such as self-cleaning, load capacity, reducing coefficient of friction). Manufacturing of natural inspired surface requires having a great control over the process to achieve the micro or nano features on the natural surfaces. Hence, the selection of the most suitable process and optimum parameters for machining of arrays of micro or nano features at large scale is highly desirable. This study reports an overview of different micromachining processes used for texturing on metallic surfaces and research gaps to be filled in the available literature. Electrochemical micromachining has tremendous potential on account of its versatility in different applications. It is a promising and economically viable machining process for micromanufacturing industries for fabrication of micro textures and micro features on metallic surfaces. Production of textured surface at large scale requires a sustainable technology, which can serve the purpose of enhancing the performance of the surface without changing the original properties of the surface. Indeed, laser surface texturing, through-mask electrochemical micromachining, lithography, micro- or nanocasting and so on are the existing methods which involve multiple steps for generation of textured surfaces. This article also reports some original experimental investigations for generation of different kinds of micro textures on metallic surfaces, namely, arrays of micro dimples, micro channels and micro pillars using a single-step maskless electrochemical micro-texturing process with a pre-patterned micro tool.
As part of the United Kingdom’s Light Controlled Factory project, University College London aims to develop a large-scale multi-camera system for dimensional control tasks in manufacturing, such as part assembly and tracking. Accuracy requirements in manufacturing are demanding, and improvements in the modelling and analysis of both camera imaging and the measurement environment are essential. A major aspect to improved camera modelling is the use of monochromatic imaging of retro-reflective target points, together with a camera model designed for a particular illumination wavelength. A small-scale system for laboratory testing has been constructed using eight low-cost monochrome cameras with C-mount lenses on a rigid metal framework. Red, green and blue monochromatic light-emitting diode ring illumination has been tested, with a broadband white illumination for comparison. Potentially, accuracy may be further enhanced by the reduction in refraction errors caused by a non-homogeneous factory environment, typically manifest in varying temperatures in the workspace. A refraction modelling tool under development in the parallel European Union LUMINAR project is being used to simulate refraction in order to test methods which may be able to reduce or eliminate this effect in practice.
The logarithmic spiral bevel gear is a new type of spiral bevel gear and has received great attention in the industry for its excellent engineering characteristics. The objective of this study is to develop an accurate geometric model for the logarithmic spiral bevel gear. Based on the gear tooth flank formation mechanism, a conical logarithmic spiral curve with a constant spiral angle was constructed as the tooth trace curve. The profiles for the exterior and interior transverse of the tooth were built with an accurate involutes curve, with transition being circular arcs and straight lines. The first tooth model was established by sweeping the tooth profile accurately along the tooth trace curve, and the rest of the teeth were created by an array operation. The accurate three-dimensional model of logarithmic spiral bevel gear was finally obtained by means of a Boolean addition operation among all of the gear teeth and the root cone. An experimental study was carried out for such a gear whose number of teeth was 37, with modules being 4.5 mm, normal pressure angle being 20° and spiral angle being 35°. A DMU 40 monoBLOCK five-axis computer numerical control milling machine tool was used to produce the prototype, and a Zeiss CONTURA G3 three-dimensional coordinate instrument was employed to measure the exterior transverse addendum diameter. The linear error between the theoretical model value and the measured average value was 0.0027 mm, indicating the effectiveness and practicability of this modeling method, which provides an accurate geometric model for design and for subsequent tasks like computer-aided engineering analysis and manufacturing.
Mechanism of chip formation during dry machining of Ni-based super alloys needs considerable research attention as it directly or indirectly affects different aspects of machinability. Therefore, the present research work aims at understanding the mechanism of chip formation with the help of various chip characteristics during dry machining of Inconel 825, a nickel-based super alloy. The influence of multilayer coating deposited using chemical vapour deposition, cutting speed and machining duration has been investigated on types and form of chips, along with different characteristics of chip like shear band thickness, saw-tooth distance, equivalent chip thickness, saw-tooth angle and chip segmentation frequency. Chip–tool contact length, hardness and crystallographic orientation (through X-ray diffraction) of chip have also been studied. Furthermore, different machining characteristics such as cutting force, apparent coefficient of friction and cutting temperature have also been determined for explaining the mechanism of various aspects of chip formation. The results indicated that coated tool restricted sharp increase in shear band thickness with cutting speed and resulted in reduction in saw-tooth distance, saw-tooth angle, equivalent chip thickness, chip hardness and deformation on grains while exhibiting increase in chip segmentation frequency in comparison with its uncoated counterpart.
This article is aiming at solving an allocation-decision problem of lot-sizing outsourcing orders between core enterprises and multiple cooperative suppliers in service-oriented manufacturing. A one-to-many cooperative stackelberg-game model which is a double-layer framework is proposed in order to obtain an optimal price and delivery time. The upper level dynamic stackelberg sub-game is designed for decision optimization problems of lot-sizing outsourcing orders between an upper level core enterprise and a lower level suppliers’ alliance. The lower level static sub-game is designed for obtaining maximum benefit of the suppliers’ alliance from lot-sizing outsourcing orders. In the game model, the leader is the core enterprise, and the follower is the suppliers’ alliance. Moreover, cost and profit are, respectively, mapping to their revenue functions. A two-level nested solution algorithm using genetic algorithm is proposed to solve the game model. Then, an equilibrium solution of this one-to-many stackelberg-game model is acquired. The analytic hierarchy process method based on contribution degree of each supplier is used for allocating profit reasonably. Finally, an example of lot-sizing outsourcing orders of gear parts validates the feasibility of the game model and its resolving algorithm. The results prove rationality of the proposed game model and correctness of the algorithm.
Nowadays, manufacturing enterprises, as larger energy consumers, face the severe environmental challenge and the mission of reducing energy consumption. Therefore, how to reduce energy consumption becomes a burning issue for manufacturing. Production scheduling provides a feasible scheme for energy saving on the system level. However, the existing researches of energy-saving scheduling rarely focus on the permutation flow line scheduling problem. This article proposes an energy-saving method for permutation flow line scheduling problem. First, a mathematical model for the permutation flow line scheduling problem is developed based on the principle of multiple energy source system of the computer numerical control machine tool. The optimization objective of this model is to simultaneously minimize the total flowtime and the fixed energy consumption. Since permutation flow line scheduling problem is a well-known NP-hard problem, the non-dominated sorting genetic algorithm II is adopted to solve the multi-objective permutation flow line scheduling problem. Finally, the effectiveness of this method is verified by numerical illustration. The computation results show that a significant trade-off between total flowtime and fixed energy consumption for the permutation flow line scheduling problem, and there would be potential for saving energy consumption by using the proposed method.
Disassembly levelling is to determine disassembly structures that specify components to be obtained from end-of-use/life products, and disassembly lot-sizing is to determine the timing and quantity of disassembling end-of-use/life products to satisfy the demands of their components. As an extension of the previous studies that consider them separately, this study integrates the two problems, especially in the form of multi-period model. Particularly, this study considers a generalized integrated problem in which disassembly levels may be different for the products of the same type. To describe the problem mathematically, we develop an integer programming model that minimizes the sum of setup, operation and inventory holding costs. Then, due to the problem complexity, a heuristic algorithm is proposed that consists of two phases: (a) constructing an initial solution using a priority-based greedy heuristic and (b) improving it by removing unnecessary disassembly operations after characterizing the properties of the problem. To show the performance of the heuristic algorithm, computational experiments were performed on various test instances and the results are reported.
Process planning and job shop scheduling problems are the two classical but crucial activities in manufacturing system. With the approach of integrated process planning and scheduling, the two actual activities are combined to conduct operation selection and operation sequencing with the constraints of practical job shop status. In this article, a quantum-inspired hybrid algorithm with the objective of minimum makespan is proposed, aiming to solve integrated process planning and scheduling problems in dynamic manufacturing systems. A hybrid-coding representation is suggested, which is a three-layer structure in numerical representation and Q-bit representation adopted from quantum-inspired evolutionary algorithm. Based on the hybrid-coding representation, customized converting and repairing rules and methods are presented to generate feasible individuals. Q-gate rotation and group leader optimization algorithm are integrated systematically for the population evolution to accelerate the convergence speed of the proposed algorithm. In order to increase the diversity of population, a chaotic map called logistic map is introduced, bringing the stochastic initial individuals. Experiments show that the proposed hybrid algorithm can generate outstanding outcomes for integrated process planning and scheduling instances.
The article presents the results of experimental investigations to determine the effect of active surface morphology of grinding wheels with a zone-diversified structure on the form and size of chips generated during traverse internal cylindrical grinding of 100Cr6 steel. In the grinding process involving grinding wheels with a zone-diversified structure, chip formation phenomena differ in the rough and finish grinding zones of the tool. In order to expand one’s knowledge of this phenomena, the microtopography measurements of the grinding wheel active surface in the rough and finish grinding zones were made, as well as scanning electron microscopic observations of these areas after the dressing cut and following internal cylindrical traverse grinding. The conducted studies showed that chips in the rough grinding zone of the grinding wheel active surface are usually several hundred micrometers in length. In the finish grinding zone, however, mainly micro-chips were generated whose length does not exceed 100 µm (usually around 10 µm in length). In the rough grinding zone, shearing-type and flowing-type chips dominate with a few examples of spherical melted chips. Moreover, in the finish grinding zone, mainly slice-type and knife-type micro-chips were observed.
Tailored structures of Ni-Ti shape memory alloys for micro-electro-mechanical systems can be fabricated using laser additive manufacturing, and requisite homogeneous microstructure for predictive design and fabrication of micro-electro-mechanical systems devices can be achieved by annealing. Investigation has been performed on the laser annealing of laser additive–manufactured Ni-Ti structures using a pulsed green laser through numerical simulation and experimental studies. The parametric dependence showed that a laser energy density of 1100 mJ cm–2 has a considerable influence in annealing of Ni-Ti structures. The surface morphology, phase transformation temperature and microstructure of laser-annealed Ni-Ti structures were studied with scanning electron microscopy, differential scanning calorimetry, X-ray diffraction and atomic force microscopy. Laser energy density of 1100 mJ cm–2 was used for annealing the samples as identified in the simulation. Surface annealing of Ni-Ti led to a uniform surface of the material with an increase in grain size and surface roughness. A decrease in the micro-hardness of the samples was obtained as a result of laser annealing. Thus, the investigations demonstrated the improved properties of laser additive–manufactured Ni-Ti structures by laser annealing.
With the continuous innovation of technology, automated guided vehicles are playing an increasingly important role on manufacturing systems. Both the scheduling of operations on machines as well as the scheduling of automated guided vehicles are essential factors contributing to the efficiency of the overall manufacturing systems. In this article, a hormone regulation–based approach for on-line scheduling of machines and automated guided vehicles within a distributed system is proposed. In a real-time environment, the proposed approach assigns emergent tasks and generates feasible schedules implementing a task allocation approach based on hormonal regulation mechanism. This approach is tested on two scheduling problems in literatures. The results from the evaluation show that the proposed approach improves the scheduling quality compared with state-of-the-art on-line and off-line approaches.
Polymer composite materials can be produced by reinforcing carbon black, carbon fiber, graphite, graphene, metals and metal oxides, nanotubes, and so on. These types of composite materials can be employed in applications demanding electrical conductivity besides high specific strength and stiffness properties of polymer materials. In the literature, there is a lack of knowledge on the examination of drilling of particle-reinforced composite materials. In this study, drilling of pure polypropylene and carbon black–reinforced polypropylene composite material was investigated at different drill point angles, cutting speeds, and feeds. The cutting temperature of drill point and surface roughness of holes were examined. The experimental studies were designed by L27 full-factorial design, and analysis of variance statistical method was performed. According to the results, cutting temperature increased and surface roughness decreased with the increase in the cutting speed and feed and decrease in the drill point angle.
Ductile iron can be produced to have different properties through proper control of heat treatments and additives that is directly related to the microstructure. The nodular form of the graphite imparts beneficial characteristics for this alloy. The purpose of this research is to investigate the effect of main process parameters, namely, feed rate, depth of cut, cutting speed and tool node radius on the surface roughness in nodular cast iron during turning operation. The concerned cutting tools used are turning tools with carbide inserts with tool nose radius of 0.4 and 0.8 mm. Three levels of cutting speed, feed rate and depth of cut are investigated. Surface roughness Ra was measured for each combination of machining conditions. Design of experiment tools were implemented to develop a model that relates the process variables to the resulting surface roughness. The model revealed the individual contribution of each parameter as well as the interaction among parameters to impart a change on the surface quality. The results showed that the feed rate and tool nose radius had the major contribution and to a lesser extent comes the role of cutting speed and depth of cut for controlling surface roughness. Minimum roughness was achieved at higher cutting speed, lower feed rate and lower depth of cut for the higher nose radius. Metal removal rate, as a measure for productivity, was also calculated and multi-objective optimization was conducted to minimize Ra and maximize metal removal rate simultaneously. Optical microscopy, on the effect of nose radius for the optimum process parameters for minimum Ra, revealed that for lower nose radius there are more occasions of graphite pullouts that affected the surface quality adversely.
In this article, the effect of abrasive types on the abrasive flow machining process was investigated. Four groups of abrasive media were prepared with different types of abrasives: SiC, AL2O3, B4C and Garnet. An experimental study was performed on DIN 1.2379 tool steel. The specimens were cut using wire electrical discharge machining and finished with the abrasive flow machining process. The results show that the white layer that formed during wire electrical discharge machining was successfully removed by abrasive flow machining in a few cycles. Although the surface roughness improves with similar trends for all media groups, the results show that the media prepared with B4C and SiC have more surface improvement than the Al2O3 and Garnet ones. The resulting average surface roughness (Ra) values are comparable to the surface quality of those obtained from lapping and super-finishing. The material removal is directly related to the hardness of the abrasive.
Aluminum has been increasingly used in automotive and aerospace applications due to its beneficial specific strength and chemical properties. Due to its extensive use, machining of aluminum parts has become specifically significant in recent years. One important aspect of machining is the surface quality represented by the surface roughness values. In this article, the effect of equal-channel angular pressing on the surface roughness (Ra, Rq, Rt and Rz) of commercial purity aluminum machined by turning was studied. Five starting material conditions, defined as the annealed and equal-channel angular pressing processed up to four passes, were investigated. The independent variables were the cutting speed, depth of cut and feed rate. The fourth parameter (number of equal-channel angular pressing passes) was considered as categorical factor and, hence, was not included in the mathematical model. A full central composite circumscribed design matrix was built to allow the optimization of surface roughness using response surface methodology. The significance of process parameters and their interactions in estimating surface roughness was investigated using analysis of variance. The two parameters, with significant effect on surface roughness, were found to be the feed rate and number of equal-channel angular pressing passes. Minimum depth of cut (0.15 mm) and minimum feed rate (0.05 mm/rev) are needed to achieve minimum surface roughness parameters: Ra (0.06 µm), Rq (0.057 µm) and Rz (0.71 µm) and Rt (1.2 µm). The cutting speed, for these optimum roughness values, ranged from 207.5 m/min for Ra to 193 m/min for Rz. The optimum roughness values were generally achieved with the higher strength materials. Optimum values for Ra, Rq and Rz happened at the four equal-channel angular pressing passes–processed material, while the optimum value of Rt happened at the three equal-channel angular pressing passes–processed material.
Electric discharge machining has been established as an effective alternative process to conventional material removal processes for machining reinforced metal matrix composites. Wire cut electric discharge machining holes were produced in a metal matrix composite (10 vol% of SiC in Al6061), which were then investigated to determine the machinability of the material using this process. It was observed that the input factors such as the size of reinforced particles, wire tension and pulse-on time significantly affect diameter error, circularity and surface roughness. Pulse-on time, the interaction between pulse-on time and wire tension contribute to the maximum diameter error. The wire tension is the most significant factor to circularity, which is followed by the interaction between pulse-on time. In particular, wire tension with low and high tensions results in poor circularity. It has been found that there are more surface defects encountered when particle sizes are smaller, and circularity is improved when particles are in a medium size. In addition, the surface defect is reduced as the particles increase the melting resistance of the surface. The higher pulse-on time leads to higher heat and more time to degrade the surface. Therefore, low pulse-on time and wire tension gave better surface finish.
The material removal phenomenon of sparking and melting in micro-electro-discharge-milling process occurs at inter-electrode gap of dimension less than 50 µm. The behavior of fluid flow properties at inter-electrode gap is not well discussed in the literature and its information will be useful to understand the material flow behavior and tool wear in micro-electro-discharge-milling process. Based on our previous findings, it was well recognized that tool rotation is an inherent part of micro-electro-discharge-milling and directly influences debris flushing and redeposition. Also for a stable machining performance, flow of dielectric will play an important role in flushing away debris from the gap. The objective of this work is to investigate the fluid flow along the inter-electrode gap and to study its effect on debris movement and molten metal redeposition. The fluid flow along the narrow gap of micro-electro-discharge-milling process for different machining conditions is analyzed by computational fluid dynamics simulation. By particle simulation, the effect of different sized particles formed at various positions and their subsequent movement was also analyzed. The computational fluid dynamics analysis results were validated with scanning electron micrographs obtained for various machining conditions of the experiments. The effect of inlet nozzle velocity, tool rotation and size of electrode gap on the dielectric fluid flow was primarily reported and the findings were later superimposed on particle injection velocity to determine the movement of debris along inter-electrode gap. The effect of debris movement on redeposition at workpiece/tool surface and its ejection from inter-electrode gap is recounted.
Electrodes made of graphite material are widely used for electro discharge machining. The performance of physical vapor deposition AlTiN and chemical vapor deposition diamond-coated carbide end-milling tools in dry high-speed milling of electro discharge machining graphite was investigated, also adopting an uncoated one as a comparison. The quality of as-deposited diamond film was evaluated by Raman spectroscopy. The adhesion between the coating and the substrate was assessed by indentation test. The tool life and wear mechanism of the milling tools, the cutting forces during tests, as well as the roughness of processed surfaces were systematically studied. It is found that the diamond coating has lower adhesion than the AlTiN coating under the same load. Coating delamination and chipping, irregularly zigzag side flank wear, concave structure on the cutting edge are primary wear patterns for the diamond-coated tool. While different primary wear patterns, including uniform polishing abrasive flank wear and crater rake wear, are observed on the AlTiN-coated tool. Besides, the total cutting force of the diamond-coated tool is larger than that of the AlTiN-coated tool when the diamond-coated tool side flank wear value reaches 0.06 mm, attributed to the different wear patterns. Another notable result is clarified that the chipping of the diamond coating can cause significant increment in the feed force, radial force and worked surface roughness.
Deterministic polishing as the final step of freeform surface machining can acquire preferable form accuracy. In this article, a deterministic polishing model based on iterative intersection tool path is presented to meet the requirement of high-form accuracy in freeform surface. In the polishing process, on-machine measurement and point set registration method are adopted for installation error extraction and form error calculation. The iterative polishing can be finished without discharging of workpiece by on-machine measurement strategy, which will reduce the processing time and improve the machining efficiency. In addition, a boundary extension method is employed to diminish the surface edge collapse generated by edge effect. Finally, the polishing experiment of freeform optical surface in an off-axial three-mirror anastigmat imaging system is conducted to verify the effectiveness of the proposed model.
In the machine tools, tool vibration is an undesirable phenomenon which affects tool life, quality of machined surface and produces irritating noise. This tool vibration is due to the interaction between metal cutting process and forces acting on the machine tool. In this investigation, an attempt was made to reduce tool vibration during turning of hardened steel using particle and mass impact dampers. A mass impact damper used in this investigation consists of a concentrated mass made of copper mounted on the bottom of the tool holder and particle damper consists of copper particles of 3.5 mm diameter positioned along the axis of the tool holder. Particle size and its location were designed using computational analysis and impact hammer–based modal testing was performed for both dampers. When these dampers were mounted on the tool holder, particles will collide with each other and subdue the vibration produced in the tool holder. Cutting experiments were conducted to study the influence of mass and particle damping on tool vibration and cutting performance during turning of hardened AISI4340 steel using hard metal insert with sculptured rake face. From the results, it was observed that the use of mass impact and particle dampers enhances the rigidity of the tool holder which, in turn, reduces tool vibration and improves the cutting performance. Among the two dampers, it was found that the presence of mass impact damping provides superior cutting performance when compared to particle damping.
When a composite laminate is tailored to suit its design intent, it is possible to improve the individual ply shapes to reduce component mass. If the laminate is going to be manufactured using an automated deposition system such as an automated fibre placement machine, then the design of the laminate will also influence the material deposition speed. This article identifies methodologies for indicating the likely impact on automated manufacture at the design optimisation stage by evaluating the ratio of ply perimeter to ply surface area when the laminate is defined as a simplified array of cells which are filled or unfilled to create a two-dimensional representation of the ply shape. A set of recommendations are made for using the methodology for improving deposition speed.
Improvement of mechanical properties of metal strips can be achieved by producing ultra-fine grained microstructure. The equal channel angular rolling process is one of the effective severe plastic deformation techniques which can lead to proper ultra-fine grained structures. In this research, the influence of process parameters such as pre–equal channel angular rolling annealing temperature, number of equal channel angular rolling passes, routes and post–equal channel angular rolling annealing on deformation behavior of 5083 Al alloy is investigated by experimental studies and numerical simulations. Metallurgical investigations revealed that grain refinement and increased dislocation density are two effective parameters on the mechanical strength improvement. The investigation of mechanical properties demonstrated that increasing number of equal channel angular rolling passes leads to a considerable increase in yield stress, ultimate tensile strength and hardness. In contrast, elongation was dramatically reduced. Also, improvement of mechanical properties reaches saturation at a critical strain level, depending on the microstructure evolution. In addition, investigation of effects of post–equal channel angular rolling annealing on the specimens annealed at 415 °C indicated that elongation and toughness increase, accompanying with a low decrease in yield and tensile strengths and hardness. In this study, the equal channel angular rolling process was numerically simulated using ABAQUS software in two different routes for three passes. It is shown that upper roller force is increased by increasing the number of equal channel angular rolling passes, but the rate of this increase is reduced at higher passes.
In this article, a new method for the rapid and economical production of ‘nutless’ bolted joins is presented, using a combination of two hole-making techniques, namely, form drilling and form tapping. The combined method achieves a quick way for the production of threaded holes on couples of dissimilar metal alloys, as it is the case of steels and aluminium alloys. After the simultaneous form drilling on the aluminium–steel pairs and followed by form tapping, a fastener can be introduced and screwed for achieving a tight bolted joint, without any necessity of nut. However, form drilling and threading are performed consecutively in the same machine tool, reducing the whole process time. The process parameters were studied for reducing the gap between surfaces and producing a good cup for making the posterior threading. Then, mechanical testing of several test pieces resulted in a similar behaviour than traditional bolted joints. Finally, corrosion tests were performed for a better understanding of the joint manufactured. In this way, savings in time and money are derived from the application of the approach. Target markets for the new approach are the light boilermaking industry in order to eliminate either welding beads or classical bolted joints using nuts.
Needle vibration tissue cutting is a method that has been shown to reduce tissue cutting force and thereby improve needle position accuracy inside the body. Needle accuracy is crucial for minimally invasive needle operations such as the radiation cancer treatment of brachytherapy. This article uniquely determines the importance of needle geometry in minimizing cutting force in needle vibration tissue cutting. This article also determines how vibration specifically affects cutting force. This new information was found by performing needle cutting experiments with five varying conical tipped needles being inserted into ex vivo bovine liver as well as a polyurethane sheet at varying vibratory amplitudes and frequencies. Results show that applying vibration to sharper needles greatly reduced the insertion force by up to 67%, where the blunter needles saw diminishing benefits. The tissue phantom experiments showed that vibration reduced the force needed to propagate the created crack but showed no improvement over the initial puncture force. This greater understanding of needle vibration tissue cutting can lead to improved needle geometry designs that work with vibration to reduce tissue cutting force.
The aim and objectives of this article are to provide an analytical model for the incremental forming of gears along the direction perpendicular to the sheet thickness. The model allows determining the influence of the major process parameters in the indentation force and in the material volume undergoing plastic deformation during indentation by means of double-wedge gear tooth punches. Special emphasis is placed on the influence of superimposing tension stresses along the in-plane direction. The analytical model is built upon the slip-line theory under plane strain deformation conditions, and results are compared against those obtained from experiments in DC04 mild steel and from numerical simulations performed with the finite element method. Results show that the indentation force can be significantly reduced by stress superposition, and that a minimum distance from previous indentations is necessary to produce a new gear tooth in a material free from residual strains and stresses.
Bi-rotary milling head is one of the core components of five-axis machining center, and its dynamic characteristics directly affect the machining stability and accuracy. During the sculptured surface machining, the bi-rotary milling head exhibits varying dynamics in various machining postures. To facilitate rapid evaluation of the dynamic behavior of the bi-rotary milling head within the whole workspace, this article presents a method for parametrically establishing dynamic equation at different postures. The rotating and swing shafts are treated as rigid bodies. The varying stiffness of the flexible joints (such as bearings and hirth coupling) affected by gravity and cutting force at different swing angles is analyzed and then a multi-rigid-body dynamic model of the bi-rotary milling head considering the pose-varying joint stiffness is established. The Lagrangian method is employed to deduce the parametric dynamic equation with posture parameters. The static stiffness, natural frequencies and frequency response functions at different postures are simulated using the parametric equation and verified by the impact testing experiments. The theoretical and experimental results show that the dynamics of the bi-rotary milling head vary with the machining postures, and the proposed method can be used for efficient and accurate evaluation of the pose-dependent dynamics at the design stage.
This article introduces two comprehensive experimental models to predict the compressive residual stress profile induced in TC17 alloy after shot peening. Experiments are carried out utilizing one of experimental design techniques based on response surface methodology. Shot peening intensity and coverage are considered as two input parameters affecting compressive residual stress profile. The characteristic parameters model is created by regression analysis, which has the capability of predicting the four main characteristic parameters of a typical compressive residual stress profile. Based on this model, the absolute sensitivity of characteristic parameters with respect to shot peening intensity and coverage is analyzed. The sinusoidal decay function model is created with a proposition of that the compressive residual stress profile is a sinusoidal decay function of the depth beneath surface and the coefficients of this function are, in turn, functions of the two input shot peening parameters. The main advantage of sinusoidal decay function model over characteristic parameters model is that it provides the effect of shot peening parameters on the shape of the compressive residual stress profile. The two models have been checked for accuracy by two extra tests. The results show that the prediction errors of the four main characteristic parameters are within 20%, and the compressive residual stress profiles predicted by the sinusoidal decay function model are in consistent with experimental data.
The ability to predict the critical depth for ductile-mode grinding of brittle materials is important to grinding process optimization and quality control. The traditional models for predicting the critical depth are mainly concerned with the material properties without considering the operation parameters. This article presents a new critical energy model for brittle–ductile transition by considering the strain rate effect brought by the grinding wheel speed and chip thickness. The experiments will be conducted through a high-speed diamond grinder on reaction-sintered silicon carbide materials under different grinding speed and chip thickness. Through detailed analysis of the strain rate effect on the dynamic fracture toughness, a new fracture toughness model will be established based on the Johnson–Holmquist material model (JH-2) and calibrated through experiments based on the indentation fracture mechanics. Then, the new critical model for brittle–ductile transition will be established by introducing the dynamic facture toughness model considering the wheel speed and chip thickness. According to scanning electron microscope observations, the results show that ductile-mode grinding can be obtained through a combination of higher grinding speed and smaller chip thickness. Moreover, the critical value for ductile grinding of brittle materials can be improved through the elevation of the grinding speed or reduction in the chip thickness.
According to the increasing needs of three-dimensional printing technologies to satisfy high-level requirements, customization, and complicity, the quality of three-dimensional printed part becomes an important issue due to the layer-wise nature of additive manufacturing process. The objective of this study is to propose a methodology to identify the quality of three-dimensional printed parts with circular holes in the laser aided additive manufacturing process. We utilize a response surface methodology to represent the relationship between input variables (chord height tolerance and diameter of a hole) and response (geometric error) for evaluating the geometric accuracy of the three-dimensional printed parts with the diameter of holes. From the calculated response surface methodology, we conclude that the proposed methodology can be utilized as a process design guide to guarantee the quality of a part printed from the laser aided additive manufacturing process. The efficiency and limitations of the proposed methodology are verified by conducting a case study.
Machining by parallel planes is a widely used strategy for end-milling of free-form surfaces on 3-axis numerically controlled machines. In industry, this type of machining is generally performed with a hemispherical tool. However, numerous studies have shown the benefits of torus-end mills over ball-end or flat-end mills. More than anything, the machining direction has much influence on productivity while using a torus-end mill. In this context, the choice of the machining direction is of paramount importance when using a torus-end mill in the machining of free-form surfaces. This paper presents an optimization of part machining direction allowing the machining time to be minimized while respecting the maximum imposed scallop height. This optimization methodology is then applied to an industrial part and measurements are performed on this part. The study highlights the interest of optimizing the machining direction and the benefits that can be drawn with respect to machining using a non-optimized direction.
An experimental investigation of the cutting performance in hybrid laser–waterjet (or laser-assisted waterjet) micro-grooving of germanium wafers is presented, with a view to eliminate or minimize the laser-induced thermal damages to the workpiece. Various process parameters are considered, such as water pressure, laser pulse overlap, pulse energy and focal plane position. It is found that the hybrid laser–waterjet is a viable technology for micromachining of germanium with negligible thermal damage. A Raman spectroscopy study did not reveal any crystalline change in the material on the machined surfaces. The effects of process parameters on the heat-affected zone and groove characteristics are amply discussed. It is shown that good grooves of within 100 µm in top width and up to 300 µm in depth can be machined with high material removal rates, and the heat-affected zone size can be controlled to within 20 µm on each side of the grooves. Recommendations are also made on the appropriate process parameters that may be used in the process.
The optical performance of lens machined by single-point diamond ultra-precision turning can be affected by both form errors and surface roughness. The former can be characterized by the spectra of lower spatial frequencies of surface variations while the latter by much higher spatial frequencies. Fast Fourier transform method is used to analyze the surface profile and to decompose the surface features in terms of relative spatial frequencies (or periods). Most of the conventional post-machining lapping processes are aimed at improving the surface finish mainly, and the form accuracy would very likely be tempered. A lapping process with very low lapping pressure is used to study the relationship between the various spatial frequency groups with various lapping process parameters. The preferred spectral group is found to change with lapping time. As the lapping time is increased beyond a certain point, the spatial period of the preferred spectral group shifts to a lower spatial frequency region. Thus, it is possible to improve the surface finish while maintaining the form accuracy. The study would have important implications in the lapping of aspheric or freeform surfaces.
According to the correlation between product quality and equipment degradation state, an equipment maintenance policy is designed by integrating periodic equipment inspection and product quality control. In this policy, np-chart is used to monitor the abnormal shift of the product quality characteristic based on periodic inspection of the equipment. By considering the inspection result of the product quality shift and equipment degradation state, the corresponding maintenance action is chosen. Furthermore, the optimal maintenance model based on product quality control is proposed and is solved with genetic algorithm. The experimental results validated the feasibility of this model.
The aim of this research was to introduce a computational approach for prediction of the forming limit diagram of Al-Cu two-layer metallic sheets. The computational approach was based on the modified Marciniak and Kuczynski theory. In this study, the forming limit diagrams of aluminum–copper two-layer metallic sheets were obtained through the modified Marciniak and Kuczynski theory and experimental investigations. In the present modified Marciniak and Kuczynski theory, there existed four nonlinear equations which were solved simultaneously. The Quasi-Newton Method was applied for a solution to the system of equations. To verify the theoretical predictions, the experimental works were accomplished on the Al-Cu two-layer metallic sheets and a good agreement between the proposed method and experimental works was observed.
Equal channel forward extrusion is a new severe plastic deformation method that has been developed in recent years. This study investigates the effect of significant parameters on the equal channel forward extrusion pressing force. First, the process was modeled by finite element method and has been validated using experimental results. Next, response surface method and analysis of variance were applied to investigate the influences of equal channel forward extrusion parameters such as friction coefficient magnitude, length-to-width ratio and main deformation zone height on the pressing force. Finally, a new formula is presented for prediction of equal channel forward extrusion pressing force using statistical modeling.
To manufacture a steel structure, in the first step, raw steel plate needs to be cut into proper sizes. Oxy-fuel flame is widely used in the cutting process due to its flexibility with respect to accessibility, plate thickness, cost, and material handling. However, the deformation caused by the cutting process frequently becomes a severe problem for the next process in the production of steel product. To decrease the deformation, the thermo-elasto-plastic behavior of the steel plate in the cutting process should be analyzed in advance. In this study, heat sources in oxy-ethylene flame cutting of steel plate were modeled first, and the heat flow in the steel plate was then analyzed by the models of the heat sources using a numerical simulation based on the finite element method. To verify the analysis by the numerical simulation including the models, a series of experiments were performed, and the temperature histories at several points on the steel plate during the cutting process were measured. Moreover, the predicted sizes of the heat-affected zone by the numerical simulations according to the variation in the cutting parameters were compared to the experimental results. The power functions of the relationship between the sizes of the heat-affected zone and cutting parameters were obtained by the recursion analysis using the correlation between the results and parameters. The results of the numerical simulation showed good agreement with those of the experiments, indicating that the proposed models of the heat sources and thermal analysis were feasible to analyze the heat flow in the steel plate during the cutting process.
In order to increase the machining accuracy of slow tool servo turning of complex optical surface, the optimal design for tool path was studied. A comprehensive tool path generation strategy was proposed to optimize the tool path for machining complex surfaces. A new algorithm was designed for tool nose radius compensation which had less calculation error. Hermite segment interpolation was analyzed based on integrated multi-axes controller, and a new interpolation method referred to as triangle rotary method was put forward and was compared with the area method and three-point method. The machining simulation indicated that the triangle rotary method was significant in error reduction. The interpolation error of toric surface was reduced to 0.0015 µm from 0.06 µm and sinusoidal array surface’s interpolation error decreases to 0.37 µm from 1.5 µm. Finally, a toric surface was machined using optimum tool path generation method to evaluate the proposed tool path generation method.
A facile process for controllable fabrication of wetting surfaces with variable hierarchical structures on metallic substrates is proposed in this study. This process, which combines the through-mask electrochemical micromachining with hydrothermal growth method, could be applied on all kinds of type and size of conductive metal. First, the anodic dissolution process is predicted using numerical simulation and experiments. The formulation of electrolyte and the etching conditions in through-mask electrochemical micromachining are optimized. Ordered microstructures and smooth etched surface in large scale are obtained using the optimized parameters. Moreover, a technology has been explored to obtain various styles of multi-level structures through an alignment system or combining with a hydrothermal method of growing ZnO nanorods. The wetting effects of the rough three-dimensional surfaces are evaluated using a contact angle system. Furthermore, the wetting and the preliminary friction reduction effects of the rough three-dimensional surfaces are evaluated using contact angle system.
Ultra-precision raster milling induces phase changes and crystal orientation changes of Zn-Al alloy at its machined surface up to a thickness of several hundreds of nanometers. In this study, the phase change characteristics of Zn-Al alloy at different penetration depths have been discussed using X-ray diffraction and nano-indentation tests. A phase-change-distribution function to depth has been proposed to calculate phase change thickness based on the X-ray diffraction measurement, which was verified by the nano-indentation tests. It is found that phase changes sharply decrease along the penetration depth and the Bragg angle first decreases and then increases back, less than the original value. Significantly, the proposed method is nondestructive to characterize phase change characteristics and measure phase change thickness.
A cutting tool’s remaining useful life is what is left for a tool, at a particular working age, in order to reach a pre-specified level of acceptable performance. The prediction of remaining useful life is crucial in order to decrease the scrapped products or the unnecessary interruption of the machining process in order to replace the tool. Consequently, the accuracy of its estimation affects the cost of machining, particularly when the product’s material is very expensive. In this article, the remaining useful lifes of 25 identical tools are estimated during turning titanium metal matrix composites. These composites are extensively used in aerospace and aviation industries. Accurate estimation of the remaining useful life has positive impact on product quality in terms of producing the required specifications. In this article, experimental data are gathered, and the proportional hazard model are used in order to model the tool’s reliability and hazard functions with EXAKT software and then the remaining useful life curves are developed for different machining conditions, namely, the cutting speed and the feed rate. The use of the proportional hazard model is validated using a normalization process and Kolmogorov–Smirnov test. The proportionality assumption is verified using log minus log plot. The final result is the development of the curves that represent the tools’ reliability and the remaining useful life for different machining conditions of the titanium metal matrix composites.
The profile accuracy of screw rotor affects the performance of screw compressor directly. In precision form grinding, installation errors of grinding wheel are the crucial factors affecting profile accuracy of screw rotors. A numerical method for quantifying profile error of screw rotor was proposed to evaluate effects of installation errors of grinding wheel on rotor profile. Coordinate transformation and engagement theory were applied to generate rotor profile, and the error model of rotor profile was established by comparing the generated rotor profile with the original one. Furthermore, the error evaluation procedure was presented based on the discrete rotor profile points. Three kinds of installation errors of grinding wheel are analyzed including installation angle error, center distance error and axial position error in the numerical cases. By inputting installation errors of grinding wheel, the effects on rotor profile are evaluated considering both single-factor installation errors and coupled-factor installation errors of grinding wheel. The evaluated results provide a theoretical basis for error tracking and error compensation in screw rotor grinding. Grinding experiments were performed for female rotor with different installation errors. The experimental results verify the correctness of the evaluated results.
Nickel-based alloys are finding a wide range of applications due to their superior properties of maintaining hardness at elevated temperatures, low thermal conductivity and resistance to corrosion. These materials are used in aircraft, power-generation turbines, rocket engines, automobiles, nuclear power and chemical processing plants. Machining of such alloys is difficult using conventional processes. Wire-cut electrical discharge machining is one of the advanced machining processes, which can cut any electrically conductive material irrespective of its hardness. One of the major disadvantages of this process is formation of recast layer as it affects the properties of the machined surfaces. In this study, experimental investigation has been carried out to study the effect of wire-cut electrical discharge machining process parameters on micro-hardness, surface roughness and recast layer while machining Inconel-690 material. Interestingly, hardness of the machined surface was found to be lower than that of the bulk material. The micro-hardness and recast layer thickness are inversely related to the variation of process parameters. Recast layer thickness, surface roughness and hardness of the wire-cut electrical discharge machined surfaces of Inconel-690 are found to be in the range of 10–50 µm, 0.276–3.253 µm and 122–171 HV, respectively, for different conditions. The research findings and the data generated for the first time on hardness and recast layer thickness for Inconel-690 will be useful to the industry.
Copper clad polyimide is becoming a significant raw material for the manufacturing of special circuits such as antennas. Micro-milling, which provides a direct and flexible fabrication method in three-dimensional product machining, has replaced traditional processing methods such as photolithography. However, severe burr problem which leads to serious power loss due to the skin effect is encountered because of the selection of improper machining strategies and parameters. In this study, the influence of machining strategy on burr formation is investigated at first. Then, the formation mechanism for different kinds of burrs in micro-milling of copper clad polyimide is analyzed. Furthermore, the burr height prediction model is established, and the optimized processing parameters are obtained through response surface methodology, the predicted burr height is 12 µm. At last, a verification experiment is conducted with the optimized processing parameters. The machining result shows that the optimized parameter combination contains spindle speed of 36,110 r/min, feed per tooth of 0.70 µm/z and tool diameter of 200 µm. The average burr height for verification test is 13.9 µm. Because of the instability of copper layer on copper clad polyimide, the actual burr height is slightly larger than theoretical prediction. The error between predicted value and experiment value is 15.8%. What is noticeable is that before optimization, the burr height is up to 100 µm, while after optimization, it reduces to 13.9 µm which is reduced by 86.1%. The achievements in this study are of great significance for optimizing machining parameters and improving machining quality and efficiency of copper clad polyimide, especially in antennas field.
Tool wear monitoring is critical for ensuring product quality and productivity. This article presents a novel tool wear prediction model based on improved least squares support vector machine method, combined with leave-one-out technique and Nelder–Mead technique. Leave-one-out is applied to tune the regularization factor and radial basis function kernel parameter of least squares support vector machine for enhancing the global search ability. Nelder–Mead is applied to raise the local search ability. The optimized least squares support vector machine based tool wear prediction model is constructed by learning the highly nonlinear correlationships between tool cutting conditions and actual tool wear. The effectiveness of the proposed prediction model is validated by experiments. Compared with particle swarm optimization algorithm-based least squares support vector machine and basic least squares support vector machine, Nelder–Mead-leave-one-out-based least squares support vector machine demonstrates a better performance in prediction accuracy, generalization, robustness, and convergence. The average accuracy obtained in tests for tool wear prediction is above 97%. This model provides theoretical basis for the machining condition configuration in the actual processing.
Friction stir welding is a solid-state process that is gaining preference for the joining of metals with low melting points. Despite the clear advantages of friction stir welding over traditional fusion welding, voids within the weld seam arise when improper conditions are present. The work presented in this article examines the development of an automated process monitoring system for friction stir welding. The system indirectly monitors the welding torque through the supplied current to the spindle motor. To measure the current, a clamp-on current meter was used. Our results have shown that using a simple and inexpensive clamp-on current meter provides good insight into the welding torque. Examination focused on the frequency spectrum of the current. A Fourier transform decomposed the signal into various frequencies present. The results consistently showed that when no void was present, there was a component of the current’s frequency at 14 Hz. However, when the tool encountered a void, the frequency spectrum changed. The component at 14 Hz went away while content in the range of 1–4 Hz increased.
Metal matrix composites are difficult to machine in traditional machining methods. Abrasive water jet machining is a state-of-the art technology which enables machining of practically all engineering materials. This article deals with the investigation on optimization of process parameters of abrasive water jet machining of hybrid aluminium 7075 metal matrix composites with 5%, 10% and 15% of TiC and B4C (equal amount of each) reinforcement. The kerf characteristics such as kerf top width, kerf angle and surface roughness were studied against the abrasive water jet machining process parameters, namely, water jet pressure, jet traverse speed and standoff distance. Contribution of these parameters on responses was determined by analysis of variance. Regression models were obtained for kerf characteristics. Contribution of traverse speed was found to be more than other parameters in affecting top kerf width. Water jet pressure influenced more in affecting kerf angle and surface finish. The microstructures of machined surfaces were also analysed by scanning electron microscopy. The scanning electron microscopy investigations exposed the plastic deformation cutting of hybrid 7075 aluminium metal matrix composite. X-ray diffraction analysis results proved the non-entrapment of abrasive particle on the machined surface.
A novel severe plastic deformation technique entitled rubber pad tube straining is proposed suitable for manufacturing of high-strength ultrafine-grained and nanostructured thin-walled cylindrical tubes. A punch with a convex portion in the middle is pressed down into a tube constrained with a hollow cylindrical rubber supported by a rigid cylinder. Tube diameter increases and decreases incrementally when the punch is pressed down, and the rubber pressure pressed back the tube diameter to its initial size. This process was performed on a commercially pure aluminum tube. Finite element results revealed that the equivalent plastic strain of about 1 could be reached at the end of the first cycle of rubber pad tube straining while having a good strain homogeneity along the thickness and length. Experimental results showed that the yield and ultimate strengths were increased to about 172 and 182 MPa from the initial values of about 80 and 128 MPa, respectively. Also, the hardness was increased to ~55 HV from ~44 HV.
The edge chipping of holes, which is induced by mechanical machining, restricts the applications of brittle materials. Rotary ultrasonic machining is considered a suitable approach to machine holes in brittle materials with a smaller edge-chipping size. However, obvious edge chipping at the hole exit in rotary ultrasonic machining remains observable. In this study, conical diamond core drills with various characteristic angles () were designed to further reduce the edge-chipping size for rotary ultrasonic machining. Machining tests on quartz glass were conducted to evaluate the effectiveness of this new type of drill. Experimental results show that the conical drill can obviously reduce the edge-chipping size only when certain conditions are satisfied. The mechanism of edge-chipping reduction using a conical drill was revealed by the theoretical analysis and detailed observation of the thrust force and obtained cylinder. To guarantee the feasibility of the conical drill, its characteristic angle should exceed a critical value at a certain feed rate. A higher feed rate requires a higher critical characteristic angle. The other advantage of the conical drill is its ability to suppress the bad effects of increasing the feed rate on the stability of ultrasonic vibration.
The total least square method based on singular value decomposition for fitting straight line and plane surface has been developed to deal with the straightness calibration problem. Different from the ordinary least square method only taking into account the error of the dependent variable, total least square method considers the errors of all the variables in a symmetrical way. However, in practice, it is difficult to choose an optimal method for the variable errors of measurement data in an asymmetric way. This article presents an improved calibration method for straightness error of a coordinate measuring machine. The proposed method, named as improved total least square, could fit straight line and plane surface when the variables are in an asymmetric way. In improved total least square method, weight matrices with parameter set between the independent and dependent variables are introduced to augmented matrix. A procedure is developed to determine the parameter . Numerical cases and measurement experiment are given to prove the performance of improved total least square method.
Permutation flow shop scheduling is a part of production scheduling problems. It allows "n" jobs to be processed on "m" machines. All the jobs are processed in all the machines, and the sequence of jobs being processed is the same in all the machines. It plays a vital role in both automated manufacturing industries and nondeterministic polynomial hard problem. Gravitational emulation local search algorithm is a randomization-based concept algorithm. It is used iteratively as the local search procedure for exploring the local optimum solution. Modified gravitational emulation local search algorithm is used for both exploring and exploiting the optimum solution for permutation flow shop scheduling problems. In this work, modified gravitational emulation local search algorithm is proposed to solve the permutation flow shop scheduling problems with the objectives such as minimization of makespan and total flow time. The computational results show that the performance solution of the proposed algorithm gives better results than the previous author’s approaches. Statistical tools are also used for finding out a relationship that exists between the two variables (makespan and total flow time) and to evaluate the performance of the proposed approach against the previous approaches in the literature.
Milling head is an essential assembly in the five-axis computer numerical control machine tools, positioning precision of which directly affects the machining accuracy and surface quality of the processed parts. Considering the influence of nonlinear friction in the transmission mechanism and the uncertain cutting force disturbance on the control precision of the milling head, the static and dynamic performances of the milling head are analyzed; relationships among the drive torque, load torque, motion direction and system parameters are discussed; and, finally, nonlinear dynamic model of the milling head is established. A novel adaptive sliding mode control scheme based on the variable switching gain and the adjustable boundary thickness is proposed for this nonlinear dynamic model; the stability of the closed-loop system is guaranteed by the Lyapunov theory. Experimental results show that the proposed adaptive sliding mode control can reduce the chattering in the traditional sliding mode control and can achieve high control precision without knowing the boundaries of uncertainties in advance.
Angular distortion in fusion welded joints is an alarming issue which affects the stability and life of the welded structures, occurs due to the changes in the temperature gradient during the welding process. This degrades the dimensional quality of a large structure during assembly which leads to rework the products and hence decreases the productivity. Predicting the weld-induced residual deformation before the production saves the valuable time and resources for rework. The conventional coupled transient, nonlinear, elasto-plastic thermo-mechanical analysis involves huge computational time. Computing a weld sample of small size with single pass itself takes several hours, which will be a huge amount of time in case of large structures consisting of several welding passes; thus, there is a real need of an efficient alternative technique to predict the post-weld distortions. In this work, an attempt has been made to determine the deformation in a submerged arc welded structure using equivalent load technique which reduces the total analysis time by one-third of the conventional techniques in case of a small weld structure. In this proposed method, the transient nonlinear elasto-plastic structural analysis part which is the major time-consuming part of analysis has been almost eliminated. So, this method can effectively use to predict the weld-induced distortion of very large structure with a computation time almost equal to the time required for transient thermal analysis of a small weld structure only. It is not feasible to analyze such a large welded structure with conventional coupled transient, elasto-plastic, nonlinear thermo-mechanical analysis. The predicted results of distortions have been validated with the experimental as well as published results and good agreements have been found.
Radial forging was introduced to the strain-induced step in the strain-induced melt activation process to prepare high-quality semi-solid A356.2 billet for the high solid fraction compression. Then, the deformation behaviour and microstructures at different compression velocities, temperatures and deformation zones were investigated. The results showed that radial forging can induce enough strain at 60% reduction of area to prepare ideal semi-solid microstructure. The microstructure had no obvious improvement at 75% reduction of area because the distortion energy may be saturated at 60%. During compression tests, the flow stress was sensitive to compression velocity (Vc) but was insensitive to holding temperature (Th), and it obeyed the power law
The article describes fabrication of an experimental setup which could be used for electrochemical drilling process to produce micro-holes in a copper workpiece with its different variants, namely, jet electrochemical micro-drilling, air-assisted jet electrochemical micro-drilling, ultrasonic-assisted jet electrochemical micro-drilling, and pulsed direct current–jet electrochemical micro-drilling process. Process parameters like voltage, electrolyte concentration, interelectrode gap, and electrolyte pressure have been selected to find out their effects on the process responses, namely, hole taper and material removal rate in all the above process. Attachments for air assistance and ultrasonic vibration application have been fabricated and incorporated in the setup. The effects of ultrasonic vibrations and the pulsed direct current voltage on the process responses like material removal rate and hole taper have been investigated. The effect of application of ultrasonic vibrations on the electrolyte jet has been studied. The experimental findings of ultrasonic-assisted jet electrochemical micro-drilling were compared with the findings of jet electrochemical micro-drilling. Similarly, the findings of pulsed direct current–jet electrochemical micro-drilling were also compared with the results of pulsed direct current ultrasonic-assisted jet electrochemical micro-drilling experiments. It has been found that the ultrasonic vibrations have significant effect on the two process responses. From the results, it was observed that with the use of ultrasonic vibrations, the material removal rate has increased to significant level and the hole taper has been decreased than in jet electrochemical micro-drilling. Effects of the pulsed direct current voltage supply on jet electrochemical micro-drilling and (ultrasonic-assisted jet electrochemical micro-drilling) were also analyzed. Application of pulsed direct current voltage has improved the material removal rate and reduced the hole taper in jet electrochemical micro-drilling as well as in ultrasonic-assisted jet electrochemical micro-drilling. The experimental results concluded that ultrasonic assistance have generated the holes with greater material removal rate and lower hole taper and with continuous direct current and pulsed direct current voltage.
The cold ironing process of a warm forged spur gear was applied to investigate the elastic distortions arising by the behavior of die elastic expansion and gear elastic recovery in this article. An elasto-plastic finite element simulation was performed to analyze the elastic behavior characteristics of gear and die. The effects of interference between gear and die on the elastic distortions were investigated through finite element simulation and experiment, respectively. The change of geometrical profile and dimension of the gear tooth were measured; the estimated dimension of ironed gear by finite element simulation was fitted to the experimental results well within the range of 5% relative error. Furthermore, in order to improve the dimensional accuracy of final forged gear, this study proposed a die cavity compensation method to compensate cavity of the ironing die, which was obtained by shrink fitting a outer ring into the initial ironing die. The optimum radial interference between stress ring and initial shrink-fitted die was calculated based on the Lame formula and thick wall cylinder theory. Finally, an experiment according to the proposed die cavity compensation method was carried out to examine the validity of analytical results and demonstrated that predicted dimensions could be achieved and dimensional accuracy greatly improved. It was shown that the manufacture gear satisfies the IOS6 class by measuring the iron-forged gear.
The generalized module is one of the basic elements of parametric product platform, which can effectively support product variant design and mass customization design. A similarity analysis method for the non-isomorphism generalized module is proposed to support the precise configuration of product’s function, structure, and process. The structure, function, and process information of product modules are extracted from the product lifecycle management/product data management database and converted into eigenvector by range identification. Then, the parameters of different scales in non-isomorphism classes are normalized to eliminate the effect of different dimensions. The similarity measure of function and process information is completed by vector matching. The function equivalence classes and process equivalence classes are obtained using the proposed classification algorithms. The results of similarity analysis can increase the flexibility of product variant, meet the needs of customization, and thus directly support the precise configuration. Finally, the feasibility and effectiveness of the proposed method are verified by a case study of high and middle pressure valves.
The aim of this article is the investigation of the effects of tool tilt angle on the friction stir welding of aluminium to the steel butt joint. For this purpose, 1°, 2° and 3° tilt angles are selected to friction stir welding of AA1100 to A441 AISI, while the other process parameters (i.e. tool rotational speed, travelling speed, tool offset and plunge depth) kept constant. The results showed that with increasing tool tilt angle, the interaction between two metals and axial force increased. The increasing tool tilt angle caused more surfaces to mingle, internal mixing and frictional heat generation. The results of the microstructure of joints revealed that the AA1100 microstructure is more thermo-mechanically affected than A441 AISI. The AA1100 average grain sizes at stir zone were 1.2, 1.6 and 2 µm and at A441 AISI were 6, 7 and 9 µm at 1°, 2° and 3° tilt angles, respectively. The maximum tensile strength of joints was 75% of the aluminium base metal, which was produced at 2° tilt angle. The higher heat generation and axial force at upper tilt angle cause separation of the steel fragments on the aluminium matrix and formation of Al-Fe intermetallic compound. These phenomena lead to increase in the micro-hardness of the joint at the upper tool tilt angle.
Quantifying the current and expected future performance of a machining process no doubt is essential for continuous improvement of product quality and productivity. However, process capability evaluation for small batch production runs is a challenging work, because the assumptions required by traditional evaluation approaches based on statistical process control techniques are commonly not satisfied in real world. In this article, a sensitivity analysis–based process capability evaluation method for small batch production runs is proposed, and a new capability index is also presented correspondingly. In this method, an error propagation model between machining errors and input errors is first established using weighted least squares support vector machine. Then, the sensitivity distribution of machining errors versus input errors is characterized by a set of eigenvalues and eigenvectors in the variation space of input errors. Third, the safe variation space of input errors is solved according to the specification limits of quality characteristics. Finally, the process capability is evaluated by comparing the fitness between the safe variation space and the tolerance space of input errors. A practical case is addressed to validate the feasibility and effectiveness of the proposed method, and the results demonstrate that the method can measure a real small batch machining process effectively and get rid of the common assumption of independent and identical distribution, which is needed by traditional methods.
Electrical discharge machining is a non-conventional material removal process; recently, efforts have been made to use it as a surface alloying/modifying method. This study investigates and compares the micro-hardness of the surface machined by electrical discharge machining process using composite tool electrode (copper–chromium–nickel) manufactured by powder metallurgy and conventional copper tool. Design of experiment is used to find the best level of process parameters in order to achieve high micro-hardness. The machined surfaces are subsequently analyzed using different techniques like scanning electron microscopy, X-ray diffraction and energy-dispersive spectroscopy to ascertain the surface characteristics. Results indicate that the micro-hardness of the alloyed surface formed by powder metallurgy tool electrode is improved by 96.3% as compared to base material and 65.7% as compared to the surface machined by conventional copper electrode. Energy-dispersive spectroscopy of the surface machined using powder metallurgy electrode confirms significant material migration from tool and dielectric to the machined surface. The X-ray diffraction shows the formation of cementite (Fe3C), intermetallic compound of iron, chromium and nickel (FeCrNi) and chromium carbide (Cr7C3) on the surface machined using powder metallurgy electrode.
This article intends to provide an efficient modeling and compensation method for the synthetic geometric errors of large machine tools. Analytical and experimental examinations were carried out on a large gantry-type machine tool to study the spatial geometric error distribution within the machine workspace. The result shows that the position accuracy of the tool-tip is affected by all the translational axes synchronously, and the position error curve shape is non-linear and irregular. Moreover, the angular error combined with Abbe’s offset during the motion of a translational axis would cause Abbe’s error and generate significant influence on the spatial positioning accuracy. In order to identify the combined effect of the individual error component on the tool-tip position accuracy, a synthetic geometric error model is established for the gantry-type machine tool. Also, an automatic modeling algorithm is proposed to approximate the geometric error parameters based on moving least squares in combination with Chebyshev polynomials, and it could approximate the irregular geometric error curves with high-order continuity and consistency with a low-order basis function. Then, to implement real-time error compensation on large machine tools, an intelligent compensation system is developed based on the fast Ethernet data interaction technique and external machine origin shift, and experiment validations on the gantry-type machine tool showed that the position accuracy could be improved by 90% and the machining precision could be improved by 85% after error compensation.
Automation, driven by informatics, enables manufacturing companies to increase productivity and meet market demands for cost-effective and high-quality products. However, many manufacturing operations across industry verticals continue to be manual even today. One such example is the manual assembly of the final trim and wheels in an automotive production line where there is heavy reliance on human decision-making pertaining to when, where and how to install components on and inside a constantly moving vehicle body. The main aim of this work is to develop a rule-based decision support system that will enable an automation solution to make human-like decisions in moving assembly operations. The wheel loading operation is chosen as a case study and a decision support framework and tool is developed and successfully tested using multiple assembly scenarios generated from experimental data provided by gaming interface sensors installed on the laboratory-based shopfloor. The resulting decision support system has the potential to enable the automation of moving assembly operations in various sectors of the manufacturing industry.
This study explores the feasibility of applying an integrated inventory model with the consideration of incorporating production programs and maintenance to an imperfect process involving a deteriorating production system. The main target of this research is to build an integrated inventory model with the issues of backorder and repair. Additionally, our proposed model tries to provide an optimal number of shipments m and lower cost. Furthermore, this article offers the detailed discussion of two preventive maintenances of the production run period which are named as perfect preventive maintenance and imperfect preventive maintenance. Also, in this study, we develop various special cases that consider the failure rate such as Weibull, geometric and learning effect. Based on the results, the demand and production ratio influences the holding cost and purchase cost and has the highest impact on the integrated model.
Edge stretchability refers to a sheet metal’s capability to resist edge cracking during edge forming and flanging. In this article, a quantitative method has been proposed to evaluate the effect of punching or trimming of sheet metals on the degradation of their edge stretchability. This method adopts the Marciniak and Kuczynski concept to quantify edge damages due to punching or trimming. A novel index, the effective failure strain ratio, is introduced. Effective failure strain ratio is strain-based, and it is defined as the ratio of the actual edge failure strain to the theoretical edge failure strain. The algorithm to calculate effective failure strain ratio based on hole-expansion simulations is detailed. The magnitude of effective failure strain ratio depends on the damage value, which corresponds to the edge damage caused by preprocessing such as punching. Numerical studies are conducted to demonstrate the applicability of this method. The results show that the degradation of edge stretchability of materials with higher hardening exponent (n-value in power hardening law) is more sensitive to edge damage. Hole-expansion experiments using two grades of dual-phase steels are conducted to validate the conclusions deduced from the simulations. The comparison between the experimental and numerical results shows that the proposed method is able to predict phenomena appearing in the experiments. The quantitative relationship between damage value and the punching clearance has not been established in this work yet, which requires extensive experimental investigation. However, a qualitative link has been clearly demonstrated, and this method provides a new perspective to express the pre-damage and its effect straightforwardly.
The determination of forming limit curves and deformation features of AA5754 aluminium alloy are studied in this article. The robust and repeatable experiments were conducted at a warm forming temperature range of 200 °C–300 °C and at a forming speed range of 20–300 mm/s. The forming limit curves of AA5754 at elevated temperatures with different high forming speeds have been obtained. The effects of forming speed and temperature on limiting dome height, thickness variation and fracture location are discussed. The results show that higher temperatures and lower forming speeds are beneficial to increasing forming limits of AA5754; however, lower temperatures and higher forming speeds contribute to enhancing the thickness uniformity of formed specimens. The decreasing forming speed and increasing temperature result in the locations of fracture to move away from the apexes of formed specimens. It is found that the analysis of deformation features can provide a guidance to understand warm forming process of aluminium alloys.
Incremental sheet metal forming is an evolving process, which is suitable for the production of limited quantities of sheet metal components. The main advantages of this process over conventional forming processes are reduced setup cost and manufacturing lead time, as it eliminates the need of special purpose dies, improves formability, reduces forming forces, and provides process flexibility. The objective of this work is to investigate a new hybrid-forming process, which intends to combine incremental sheet metal forming with deep drawing process and has been named as "incremental stretch drawing." A number of setups and fixtures were developed to carry out experiments to achieve incremental stretch drawing and understand the mechanism of the process. This process addresses some of the challenges of incremental sheet metal forming, that is, limited formability in terms of forming depth, especially at steeper wall angles and subsequent thinning of sheet. It is observed that the proposed process is able to reduce thinning as much as about 300%, considering same forming depth for incremental sheet metal forming and incremental stretch drawing processes. Improvement in formability, in terms of forming depths, also has been observed to be near about 100% in particular cases.
In order to efficiently remove heat from the machining zone, grinding fluids are used in the majority of grinding processes. Intensive cooling periods make it possible to efficiently influence the machining heat conditions, and through lubricating fluid components, limit the friction of active cutting vertices of unspecified geometry and a frequently negative rake angle. The obtained grinding results are considerably influenced by the amount of grinding fluid and the way it is delivered, which directly influences its effectiveness in reaching the zone of contact between the grinding wheel and the machined surface. The following article presents a new solution, as far as centrifugal grinding fluid delivery is concerned, through a special grinding wheel grip and the channels formed in it. Moreover, the system recommended here is also characterized by zonal grinding fluid delivery into the grinding wheel, which is aimed at additionally increasing the efficiency of grinding fluid delivery into the grinding zone. The results of tests evaluating the effect this system has upon grinding force values are presented. The reference methods employed in these tests were centrifugal grinding fluid delivery without zonal limitation, delivering grinding fluid using the flood method, as well as dry grinding. The results of the experiment showed that using the method recommended here enables the creation of conditions in the grinding zone similar to, or even more advantageous in certain conditions, than when delivering grinding fluid using the flood method. It also leads to a general reduction in grinding fluid expenditure by as much as 10 times.
This article presents the dynamic design and thermal analysis of an ultra-precision flycutting machine tool. The hydrostatic bearings are used both in the spindle and slide to ensure the stiffness of the machine tool. The fluid–structure interaction method is used to obtain the actual clearance changes of the hydrostatic bearing. The dynamic and thermal performances of the machine tool are analyzed considering the effect of hydrostatic bearings. The influence of the thermal effect on the static and dynamic performance of the machine tool is further studied. The prototype machine tool is built. Preliminary machining trials have been carried out and provided evidence of fluid–structure interaction method being helpful to design the ultra-precision machine tool based on the hydrostatic technology.
As additive manufacturing expands from rapid prototyping into rapid production, it is becoming more important to consider the mechanical performance of candidate products in addition to their functional attributes as a prototype. This study demonstrates how a design of experiments approach can be used to optimise the tensile and notched bending properties of the materials used in the process, while also considering the time of production and material efficiency. Such an approach can allow manufacturers to optimise the build in terms of the time, cost and material properties according to the requirements of the product. The main conclusion of this study was that when considering the significant contributors, similar build parameters result in optimised properties for both specimen types. It was also found that the layer height, being insignificant to the mechanical properties of both specimens, was critical to the cost control in terms of build time and material usage. Thus, the maximum layer height could be used to incorporate cost control into the design without affecting final performance.
There are many researches in scheduling an optimal feedrate profile under various constraints by numerical calculation. A large number of discrete feedrate data points are obtained. They are inconvenient for the parametric interpolator. Therefore, these discrete feedrate data points need to be fitted by parameter curves. Different from the regular curve fitting, the inappropriate feedrate fitting method can generate larger acceleration and jerk that seriously affect the machining accuracy and stability, although the feedrate satisfies the error requirements. In order to generate a suitable feedrate profile, a segment feedrate profile fitting method using B-spline is proposed in this article. The discrete feedrate data points are segmented in the jerk discontinuous points. In each segment, the feedrate profile is fitted by the linear least squares method. These fitted feedrate profiles are combined to generate a unified feedrate profile. The unified fitted feedrate profile and the tool path trajectory are used in the controller to command the axis. In this article, the process of parametric interpolation is separated into the arc-length calculation process and the curve parameter calculation process. Using parallel computation, the two processes are calculated simultaneously in the controller, and the computational efficiency is improved. Both simulation and experiment are carried out to verify that the fitted feedrate profile satisfies the error requirements, and the novel interpolation can be applied to the controller appropriately.
TiN-coated high-speed steel drills are known to give improved performance. However, when coatings are coupled with a careful selection of drill geometry parameters, the performance can be improved further. Consequently, in this work, progression of flank wear land width on four-faceted split-point plasma nitrided high-speed steel drills with varying point and helix angles in drilling of SS304 was analyzed along with a conventional drill with a point angle of 118°. Elaborate experimentation was undertaken to test the drills and capture the effect of flank wear on the drill performance. The drills with moderate point angle of 124° outperformed other drills with point angles of 130° and 118°. As the wear progresses, the thrust and torque show a minor increase in the case of four-faceted drills as compared to the conventional drills. Abrasion and chipping were found to be the dominant wear mechanisms while drilling SS304, whereas major drill failure mechanisms appear to be excessive abrasive wear followed by chipping.
The brazeability of automotive zinc-coated steels depends on several factors. These include the morphology of the joint and the welding parameters selected. However, more fundamental material factors such as the composition of the coating, method of coating and coating thickness also have a significant effect. In this study, five commercially available and widely used automotive zinc-coated steels are investigated to assess brazeability. Surface zinc content and the coating type are shown to have a marked effect on the quality of the resulting joint. This is shown by surface analysis of the joint to determine evenness and bridging capability of the filler material and a cross-sectional analysis of the joints. Differences in wettability and contact length of the filler material and zinc-coated steel substrate are observed. It was found that electro-galvanised steel exhibited the best brazeability of the materials investigated here. Wettability of spreading angles as low as 17.3°, most uniform contact length and best bridging capability due to the filler material forming a metallic bond with the substrate were observed. However, pores were present in cross-sections. Galvannealed steel also showed good wetting with no embedded defects. Other steels used (galvanised and magnesium–aluminium zinc steels) presented problems with uniformity, high spreading angles of the filler material and poor bridging characteristics.
Distinguished with the traditional tooth flank of spiral bevel gears, an accurate spherical involute tooth profile is of obvious advantages for the design and manufacture. For obtaining the gear model with enough tooth flank accuracy, simulation and optimization methodologies of computer numerical control-milling model are proposed. Initially, it gives an identification of the spherical involute tooth flank based on an improved formation theory. A universal simulation machining of the universal multi-axis computer numerical control-milling center is proposed to obtain an initial model. Then, in order to get/for getting improved tooth flank accuracy of the initial gear model, it presents some optimization methods included in the applications which are (1) non-uniform rational B-spline reconstruction by the Skinning method and (2) an overall interpolation based on Energy method. Finally, some given numerical examples are utilized to verify the form error of tooth flank. In addition, a closed-loop experiment scheme is provided to verify the validity of proposed methods.
Fibre composite is widely used in the field of aerospace because of its excellent performance. However, during the process of fibre placement using an automated fibre placement machine, it is difficult to guarantee accurate fibre placement. To solve the problem, this study established an online detection method for fibre tow placement accuracy. It captures the image of the detection region using an industrial charge-coupled device camera, identifies those regions with gaps in the image using computer vision methods and then acquires the gap widths which are the fibre placement accuracy of each fibre tows. When the angle between upper and lower fibre tows was small, to find the position of edges in the images accurately, we presented an improved image enhancement method based on histogram stretching. The experimental results showed that this online detection method was applicable and can quickly and effectively identify the position and width of the gaps in the detection region. Furthermore, it had high resolution, which can meet the requirements of practical engineering.
Rapid tool wear is one of the major machinability aspects of nickel-based super alloys. In this article, the effect of cutting parameters on material removal rate and tool wear of a whisker ceramic insert in turning of Inconel 625 was examined. Optical microscope and scanning electron microscope were applied to measure and study tool wear mechanism. Response surface method was used to develop a mathematical model which confirmed by experimental tests. The statistical analysis done by analysis of variance showed that depth of cut is the most effective factor on the tool wear. Experiments showed that increment of feed rate had an insignificant effect on the progress of flank wear, and it is an important controlling factor when material removal rate is considered as a desired output. Finally, optimized cutting condition is presented in this work.
The process plan selection and job shop scheduling are carried out separately and sequentially in many factories and the scheduling is always conducted after the process plan of each job has been determined. In fact, the activities for the determination of process plan and the scheduling plan are coupled with each other and actually complementary. Implementation of the two activities with an appropriate collaborative approach is essential to achieve greater performance and higher productivity for the manufacturing system. In this article, a novel cross-entropy-based approach for the joint process plan selection and scheduling optimization that can assist process planning and scheduling system to achieve optimal scheduling plan and determine the operations, machine for each operation and operation sequence for each job collaboratively was proposed. In order to facilitate the manipulation and improve the optimized performance of the approach, an efficient representation scheme and a generation method for samples were developed. Meanwhile, the updating mechanism for new introduced probability distribution parameters according to which the cross-entropy procedure generates samples was established. To verify the adaptability and performance of the proposed approach, experimental studies were conducted and comparisons were made between this approach and some previous methods. The experimental results indicate that the proposed approach is an alternative and acceptable method to solve the joint process plan selection and scheduling optimization problem.
Shaped metal deposition is a relatively new additive layered manufacturing method. It is a novel technique to build net-shaped or near-net-shaped metal components in a layer-by-layer manner via applying metal wire and selection of a heat source such as laser beam, electron beam, or electric arc. It is a manufacturing method used for production of complex featured and large-scaled parts, especially in aerospace and metal-die industries. This method can lower the cost of fabricated parts by reducing further machining and finishing processes and shortening lead time. This article presents a comprehensive literature review on shaped metal deposition, and it mainly aims to highlight some of the areas which were reported by the researchers in this field to give an extensive overview of shaped metal deposition processes, classification of its methods, and their applications. The presented literature review covers extensive details on microstructure, mechanical properties, and residual stresses induced in the metallic parts produced by various shaped metal deposition techniques as well as fabrication of dual-material parts. Additionally, grain refinement of the deposition morphologies using various techniques, especially the arc pulsation process, was mentioned. This study demonstrates that shaped metal deposition method using wire can be considered as a distinctive low-cost method for fabricating large-scaled components due to high deposition rates, high efficiencies, and dense part production capabilities. However, the accuracy and surface finish are less compared to laser and electron beam melting methods.
This article presents a new approach for obtaining unique dimensioning for each part and building a full-dimension model of assembly dimensions by describing the formative paths of functional dimensions in an assembly. According to the structure and the functional dimensions of an assembly, as well as the principles that ‘the path should be the shortest’, ‘high precision should be given priority’ and ‘one surface can appear only once in the path graph’, the shortest path graph of the functional dimensions can be established first, ensuring that every functional dimension has minimum accumulative errors. The revised path graph is obtained by revising the shortest path graph according to structural characteristics, inspection and dimensioning regulation of parts. In this way, unique dimensioning is achieved for each part, and a full correlative dimension model can be established. A gearbox assembly and a ball screw assembly are used to verify the proposed method, but this article discusses only the assembly that is generally located in a certain direction. Over-location, planar or spatial assemblies require further research.
Lean proliferates the value-adding work by eliminating wastes and reducing incidental and non-value-adding work to a certain possible extent. Waste can be defined as anything other than the essential resources of people, machines, and materials that are needed to add value to the product. According to the lean concept, any action which does not directly enhance product’s value can be considered as waste. Analysis of lean waste issues is one of the primary steps to implement lean principles in many industries and the same is applicable for the foundry industry as well. The purpose of this article is to investigate the importance of various lean waste issues in Indian foundry industry for improvement in productivity and elimination of wastes, thereby initiating lean implementation. For the purposes of this study, we employed the survey questionnaire method to collect data against 17 lean waste issues from 71 middle- to senior-level professionals belonging to Indian foundry industry. The survey instrument of lean waste issues is developed based on a number of sources from the literature and formal discussions with academicians and foundry industry professionals. The responses were received on a 5-point Likert scale ranging from never found to mostly found. Descriptive statistics is employed to find out the relative significance of lean waste issues. Exploratory factor and reliability analyses are conducted to obtain and validate constructs and measure each construct’s Cronbach’s alpha. Finally, the study concludes that there is a need for elimination of lean waste issues to implement lean manufacturing and fulfil the requirements of Indian foundry industry.
To an aircraft, the accuracy of aerodynamic configuration has a direct influence on flight performance. To improve the assembly accuracy of aircraft wing components, two kinds of positioning method and the corresponding assembly precision are studied, and a low-cost flexible assembly tooling system for different wing components is proposed. First, the article analyzes the technological characteristics of airplane wing skin and determines the assembly requirement. Second, positioning method based on contour boards and coordination holes and their assembly precision are researched. Third, to verify the positioning method and the algorithm of assembly precision calculation based on coordination holes, a locating unit with three motion axes is designed and manufactured. Fourth, experimental verification is done and the corresponding results are analyzed. Experiment results showed the assembly precision based on coordination holes has an improvement of 24% contrasting with the precision based on contour boards, and the assembly productivity is increased by 60%. The flexible assembly tooling system also has a demonstration effect for other flexible assembly tooling within the aerospace industry.
Indirect tool condition monitoring in end milling is inevitable to produce high-quality finished products due to the complexity of end-milling process. Among the various indirect tool condition monitoring techniques, monitoring based on image processing by analyzing the surface images of final product is gaining high importance due to its non-tactile and flexible nature. The advances in computing facilities, texture analysis techniques and learning machines make these techniques feasible for progressive tool flank wear monitoring. In this article, captured end-milled surface images are analyzed using gray level co-occurrence matrix–based and discrete wavelet transform–based texture analyses to extract features which have a good correlation with progressive tool flank wear. Contrast and second diagonal moment are extracted from gray level co-occurrence matrix and root mean square and energy are extracted from discrete wavelet decomposition of end-milled surface images as features. Finally, these four features are utilized to build support vector machine–based regression models for predicting progressive tool flank wear with 94.8% average correlation between predicted and measured tool flank wear values.
Metallic parts having open cell porous regular interconnected metallic structure of predetermined unit cell are being fabricated using metal powder–based rapid prototyping machines. These machines are capital intensive. All porous structures including open cell porous regular interconnected metallic structure have less density, so they lack in strength problems as compared to the solid structure. The strength of open cell porous regular interconnected metallic structure can be enhanced by providing solid inner core. In this study, a cost-effective technique has been developed to fabricate open cell porous regular interconnected metallic structure with solid core using ceramic powder–based three-dimensional printing machine and pressureless sintering. In this work, two approaches of fabrication were developed. In the first approach, only spherical metal powder was used, while in the second approach, a solid metallic rod along with spherical metal powder was utilized. Interconnected porosity and sinter density of the fabricated specimens were measured using Archimedes’ principle. The characterization was done using microstructure analysis, energy dispersive analysis, scanning electron microscopy and X-ray diffraction analysis. Mechanical properties of developed structures were determined using tensile, compressive and impact tests.
Instantaneous undeformed chip thickness is one of the key parameters in modeling of micro-milling process. Most of the existing instantaneous undeformed chip thickness models in meso-scale cutting process are based on the trochoidal trajectory of the cutting edge, which neglect the influences of cutter installation errors, cutter-holder manufacturing errors, radial runout of the spindle and so forth on the instantaneous undeformed chip thickness. This article investigates the tooth trajectory in micro-milling process. A prediction model of radial runout of cutting edge is built, with consideration of the effects of the extended length of micro-milling cutter and the spindle speed. Considering the effects of cutting-edge trochoidal trajectory, radial runout of cutting edge and the minimum cutting thickness, a novel instantaneous undeformed chip thickness model is proposed, and the phenomenon of single-tooth cutting in micro-milling process is analyzed. Comparisons of cutting forces under different chip thickness models and experimental data indicate that this new model can be used to predict cutting forces.
In this article, a research was conducted on the effects of the precession mechanism error on polishing spot, and it is helpful for optimizing the mechanism. In the research, an error model was built to analyze the error caused by gravity and polishing force on the accuracy of the mechanism, finite element analysis and MATLAB simulation were carried out based on the error model to estimate the effects, and, finally, an experiment was conducted to test the simulation result. It was found that the precession mechanism error mainly has an influence on the position of polishing spot in x and y directions. Simulation results show the position error up to –698.7 µm in y direction and –88.5 µm in z direction under free condition, while in polishing process, the error decreased 588.4 µm in y direction and 26.7 µm in z direction. The size of single polishing spot decreased 2.67%, while the size of four-step tilted polishing spot and continuous polishing spot increased 0.66% and 6.78%, respectively. Through experiment, it can be seen that the size of the polishing spot is also affected by the inflation pressure in bonnet tool, rigidity of bonnet tool, tool clamping error, and mechanism processing error.
Casting simulation softwares are increasingly being used in modern foundries and metal casting industries. Softwares simulate the casting process in a virtual domain and provide insight into mold filling, solidification and cooling, and casting defects. Casting simulations allow designers to model, verify, and validate the process followed by optimization of design and process parameters before they actually put into practice. This article aims at exploring the methods of modeling and simulation of metal casting processes with reference to some related case studies. Most commonly available casting simulation softwares and the underlying mathematical models used are briefly introduced. Casting process simulation together with the results obtained is well explained. Case studies from the literature revealed that simulation tools are playing a vital role in producing high-quality defect-free cast products by providing an in-depth understanding of mold filling and solidification, gating, runner and feeding system design, and other process parameters. Recent efforts on integrating the casting simulations to mechanical performance simulations are discussed which is quite promising in predicting the service life of cast products. It is concluded that simulations have been well established in metal casting processes and more developments in simulation tools are needed for reliability prediction of castings.
Ti6Al4V is the most widely used titanium alloy and is a demanding material in applications requiring high specific strength and corrosion resistance, that is, aerospace, automobile and biomedical industries. However, the poor machinability of this alloy, resulting from its low thermal conductivity, high hardness at elevated temperatures, high chemical reactivity with the cutting tool and low elastic modulus, restricts its usage. As a result, the tool life in machining of Ti6Al4V is substantially less than conventional materials such as steel and aluminium. This work reviews the various techniques employed in improving the machinability of Ti6Al4V alloy, from the perspective of cutting tool technology. The focus is onto the parameters affecting tool life in machining of Ti6Al4V alloy with some trending techniques and their feasibility, considering the economics to develop the best techno-economic method.
Universal machine tool settings with higher-order motion coefficients are developed to make accurate modification considering the actual machine geometric error compensation for spiral bevel and hypoid gears. First, the universal machine tool settings are exploited for the identification of the real tooth flank form error. Furthermore, the error sensitivity analysis method and an improved Levenberg–Marquardt algorithm with a trust-region strategy are utilized to obtain the solution of modification amount. Finally, a higher-order modification methodology for the universal machine tool settings is proposed which mainly covers three vital parts: (a) optimized selection of the modification settings, (b) modification of universal machine tool settings, and (c) machine geometric error compensation. Especially, a higher-accuracy fitting method for the form error tooth flank is investigated. Some numerical examples verify that the tooth flank form error after higher-order modification can reach less than 0.5 µm or even a smaller one, and the position error after compensating process spindle can be reduced from 0.0044861° to 0.0009232°. In addition, given experimental result can validate the feasibility of the proposed methodology.
Ultrasonically assisted turning is one of the modern machining processes developed in recent decades to facilitate machining of hard-to-cut materials which are widely used in different industries. Cutting tool wear is one of the main problems in machining of hard materials which has necessitated implementation of modern machining processes such as ultrasonically assisted turning. Due to vibro-impact conditions, cutting tool failure takes place when ultrasonically assisted turning is applied for hard and brittle materials. In fact, microchipping takes place in the tool nose after machining of short length, so sharp cutting edge fails at the early stages of cutting. Therefore, if the sharpness of cutting edge is removed before the machining, the fracture of cutting edge, caused by vibro-impact condition, will be eliminated. The aim of this research is to investigate the tungsten carbide tool flank wear in ultrasonically assisted turning of hardened alloy steel in comparison to the conventional turning. Therefore, a proper experimental ultrasonic vibration configuration was designed to apply the ultrasonic vibrations to the turning tool along cutting direction. Experiments were carried out for different cutting speeds below the critical speed in ultrasonically assisted turning. Application of the tool with modified specifications led to make an initial wear on tool flank, but finally a significant improvement of tool wear was observed.
The manufacture of highly complex and accurate part geometries with reduced costs has led to the emergence of hybrid manufacturing technologies where varied manufacturing operations are carried out in either parallel or serial manner. One such hybrid process being currently developed is the iAtractive process, which combines additive (i.e. fused filament fabrication, which is sometimes called fused deposition modelling. However, the latter term is trademarked by Stratasys Inc. and cannot be used publicly without authorisation from Stratasys) and subtractive (i.e. computer numerical control machining) processes. In the iAtractive process production, operation sequencing of additive and subtractive operations is essential. This requires accurate estimation of production time, in which the fused filament fabrication build time is the determining factor. There have been some estimators developed for fused deposition modelling. However, these estimators are not applicable to hybrid manufacturing, particularly in process planning, which is a vital stage. This article addresses the characteristics of fused filament fabrication technologies and develops a novel and rigorous method for predicting build times. An analytical model was first created to theoretically analyse the factors that affect the part build time and was subsequently used to facilitate the design of test parts and experiments. The experimental results indicate that part volume, interaction of volume and porosity and interaction of height and intermittent factor have significant effects on build times. Finally, the estimation algorithm has been developed, which was subsequently evaluated and validated by applying a wide range of identified influential factors. The major advantage of the new proposed algorithm is its ability to estimate the build time based on simple geometrical parameters of a given part. The key factors that drive the algorithm can be directly obtained from part dimensions/drawings, providing an efficient and accurate way for fused filament fabrication time estimation. Test part evaluations and analysis have clearly demonstrated that estimation errors range from 0.1% to 13.5%, showing the validity, capability and significance of the developed algorithm and its applications to hybrid manufacture.
Due to the international business competition of modern manufacturing enterprises, production systems are forced to quickly respond to the emergence of changing conditions. Production control has become more challenging as production systems adapt to frequent demand variation. The neuroendocrine system is a perfect system which plays an important role in controlling and modulating the adaptive behavior of organic cells under stimulus using hormone-regulation principles. Inherited from the hormone-regulation principle, an adaptive control model of production system integrated with a backlog controller and a work-in-progress controller is presented to reduce backlog variation and keep a defined work-in-progress level. The simulation results show that the presented control model is more responsive and robust against demand disturbances such as rush orders in production system.
To improve the accuracy, generality and convergence of thermal error compensation model based on traditional neural networks, a genetic algorithm was proposed to optimize the number of the nodes in the hidden layer, the weights and the thresholds of the traditional neural network by considering the shortcomings of the traditional neural networks which converged slowly and was easy to fall into local minima. Subsequently, the grey cluster grouping and statistical correlation analysis were proposed to group temperature variables and select thermal sensitive points. Then, the thermal error models of the high-speed spindle system were proposed based on the back propagation and genetic algorithm–back propagation neural networks with practical thermal error sample data. Moreover, thermal error compensation equations of three directions and compensation strategy were presented, considering thermal elongation and radial tilt angles. Finally, the real-time thermal error compensation was implemented on the jig borer’s high-speed spindle system. The results showed that genetic algorithm–back propagation models showed its effectiveness in quickly solving the global minimum searching problem with perfect convergence and robustness under different working conditions. In addition, the spindle thermal error compensation method based on the genetic algorithm–back propagation neural network can improve the jig borer’s machining accuracy effectively. The results of thermal error compensation showed that the axial accuracy was improved by 85% after error compensation, and the axial maximum error decreased from 39 to 3.6 µm. Moreover, the X/Y-direction accuracy can reach up to 82% and 85%, respectively, which demonstrated the effectiveness of the proposed methodology of measuring, modeling and compensating.
Aluminum alloys, due to lightweight, are widely used in aerospace and automotive industries. However, the low strength of aluminum has hindered its application. The strength of aluminum can be improved in many ways. One of them is decreasing the average grain size of metal by applying sever plastic deformation methods. Equal channel angular pressing is the most functional technique of sever plastic deformation producing ultra-fine-grained metals. Using post-process methods such as electrical discharge machining to manufacture industrial parts of ultra-fine-grained material is very conventional. The recast layer which is the consequence of electrical discharge machining process may cause undesirable influence on the surface of ultra-fine-grained aluminum. In this article, the recast layer and the heat-affected zone of electrical discharge machining of ultra-fine-grained aluminum are investigated. The thickness of recast layer, heat-affected zone and micro-cracks is observed using scanning electron microscopy and optical microscopy. In addition, the phase composition and the hardness of the recast layer and heat-affected zone are investigated by applying X-ray diffraction technique and micro-hardness test. These experiments are also repeated for the coarse-grain aluminum, and the results are compared with ultra-fine-grained aluminum. Results show that the electrical discharge machining deteriorates the surface integrity of the ultra-fine-grained aluminum rather than coarse-grain aluminum.
In the field of composite technology, inefficient and poor designs of twist drills contribute immensely to the challenges facing drilling of composite materials. An attempt to report some of the drill design methods and their inherent challenges confronting composite machining necessitates the writing of this article. A critical review has been conducted to offer a clear understanding of the current advances in the field of mechanical drilling of composite materials, focusing on geometry, material and parametric tool designs. The inter-dependable effects of thrust force, cutting speed, feed rate, cutting force and torque on drill design are similarly reviewed. This article also reveals other associated issues facing composite drilling including delamination, surface roughness, rapid tool wear and drill breakage. Well-designed drill geometry and good knowledge of drilling parameters afford the producers of polycrystalline diamond, carbide and high-speed steel tooling materials better opportunity of developing a drill that will minimise delamination of the reinforced composites and tool wear and produce a high-quality surface. Twist drill manufacturers and users will benefit from this article as they seek to have well-designed and improved drills.
Accomplishment of high machining rates along with good surface quality is a major concern in electric discharge machining process. Powder-mixed electric discharge machining in which suitable powder particles are impregnated in dielectric has gone forth as a potential solution to this problem. Nevertheless, challenges such as dielectric circulation, homogeneous blending of the powder particles in the dielectric, debris removal and quantity of the powder material required have to be addressed carefully before implementing this process on a large scale in the manufacturing industry. Extensive research in the field of electric discharge machining using powder-suspended dielectrics has started only in the recent years. In this article, a comprehensive review of the research going on in the field of powder-mixed electric discharge machining is presented. The emphasis is given on powder-mixed electric discharge machining mechanism, influence of powder characteristics and machining parameters on various responses. Some of the major application areas, variants of the basic powder-mixed electric discharge machining process and possibilities of further improvement are also discussed.
In this article, max–min ant colony optimization algorithm is proposed to determine how to allocate jobs and schedule tools with the objective of minimizing the makespan of processing plans in flexible manufacturing system. To expand the application range of max–min ant colony optimization algorithm, tool movement policy is selected as the running mode of flexible manufacturing system, which assumes that tools are shared among work centers and each operation is allowed to be machined by different kinds of tools. In the process of converting this scheduling problem into traveling salesman problem, disjunctive graph is modified to possess more than one path between each neighbor node. Besides providing practical methods of initializing pheromone, selecting node and calculating pheromone increment, max–min ant colony optimization algorithm employs the pheromone updating rule in max–min ant system to limit pheromone amount in a range, of which the upper and lower boundaries are updated after each iteration by formulations involving the current optimal makespan, the average number of optional tools and parameters. Finally, different sizes of processing plans are randomly generated, through which max–min ant colony optimization algorithm is proved effectively to tackle early stagnation and local convergence and thus obtains better solution than ant colony optimization algorithm and bidirectional convergence ant colony optimization algorithm.
In this investigation, the attention is focused on the minimum bending radii of 2196-T8511 and 2099-T83 Al-Li alloy extrusions. To predict the failure of Al-Li alloys, sheet and extrusion stretch bending tests are developed, carried out and simulated using finite element model. The theoretical minimum bending radius is introduced to derive a safe lower limit for the bending radius which can serve as a guideline for tool and product design. Stretch bending tests of Al-Li alloys are performed using the three-point bending test and displacement-controlled stretch bending test at room temperature. The finite element model incorporates three-dimensional solid elements and ductile damage modeling. The experimental results show that Al-Li alloy extrusions in stretch bending show three types of failures, occurring at the unbent region near the entrance of the jaws, at the region below the exit of the die and within the region in contact with the die, respectively. Comparison between predicted values and experimental results has been made, a consistent agreement being achieved, reflecting the reliability of the present model. The three types of failure mechanisms which compete with each other are tensile localization failure, die-corner failure and shear failure, respectively. Based on the analytical models, experiments and simulations, it appears that the three distinct failures need to be applied to predict the minimum bending radius and range of failures that can occur with 2196-T8511 and 2099-T83 Al-Li alloy extrusions in stretch bending.
The effects of machining parameters, such as reinforcement size, machining speed and feed rate, on tensile strength, strain at break and fractured surfaces of Al-based metal matrix composites were analysed in this present investigation. It was found that larger particles (13 µm) induce higher stiffness on machined metal matrix composite parts machined at higher speed (2500 r/min) and lower feed (200 mm/min), providing constant input parameters are of low values and vice versa. The effect of reinforcement size on tensile strength is negligible and higher speed (2500 r/min) and lower feed (200 mm/min) give higher tensile strength when constant input parameters are of low values. The higher machining speed (2500 r/min) gives higher strain at break though reinforcement size and feed rate have minor effect on strain at break when the constant input parameters are of high values. When the constant input parameters are of low values, the smaller reinforcement (0.7 µm), machining speed (1500 r/min) and feed rate (200 mm/min) give higher strain at break. Ductile fracture occurs in all cases regardless of input variables and smaller nodules were formed on fractured surface in the case of smaller particle (0.7 µm)-reinforced metal matrix composites.
A three-revolute-prismatic-spherical parallel kinematic machine is proposed as an alternative solution for high-speed machining tool due to its high rigidity and high dynamics. Considering the parallel kinematic machine module as a typical compliant parallel mechanism, whose three limb assemblages have bending, extending and torsional deflections, this article proposes a hybrid modeling methodology to establish an analytical stiffness model for the three-revolute-prismatic-spherical device. The developed analytical model is further used to evaluate the stiffness mapping of the three-revolute-prismatic-spherical module over a given work plane which is then validated by experimental tests. The simulations and experiments indicate that the present hybrid methodology can predict the three-revolute-prismatic-spherical parallel kinematic machine’s stiffness in a quick and accurate manner. The solution for eigenvalue problem of the stiffness matrix leads to the stiffness characteristics of the parallel module including eigenstiffnesses and the corresponding eigenscrews as well as the equivalent screw spring constants. Based on the eigenscrew decomposition, the parallel kinematic machine is physically interpreted as a rigid platform suspending by six screw springs. The minimum, maximum and average of the screw spring constants are chosen as indices to assess the three-revolute-prismatic-spherical parallel kinematic machine’s stiffness performance. The distributions of the proposed indices throughout the workspace reveal a strong dependency on the mechanism’s configurations. At the final stage, the effects of some design parameters on system stiffness characteristics are investigated with the purpose of providing useful information for the conceptual design and performance improvement of the parallel kinematic machine.
The essence of the "ratio data" in cellular manufacturing system has rarely been correctly emphasized since past few decades of research and study. This article is an attempt to deal with cell formation problem which exploits machine utilization percentage and eliminates the "fuzziness" on the subject of ratio data. In the course of this study, a distinctive technique is adopted based on multi-criteria decision technique with significant modifications which is experimented on test data and compared with published methodology. To verify the grouping result, a novel performance measure is proposed and elaborated analytically to establish its superiority and robustness over the earlier efficiency measures published in the past literature of cellular manufacturing system. The novelty of this research remains in eradicating ambiguities on the subject of "ratio data," imposing appropriate rules while generating the test problems, catering a unique multi-criteria decision technique–based approach and a novel performance measure for the aforesaid problem.
The optimization for multidisciplinary engineering systems is highly complicated, which involves the decomposing of a system into several individual disciplinary subsystems for obtaining optimal solutions. Managing the coupling between subsystems remains a great challenge for global optimization as the existing methods involve inefficient iterative solving processes and thus have higher time cost. Some strategies such as discipline reorder, coupling suspension and coupling ignoring can to some extent reduce the execution cost. However, there are still some deficiencies for these approaches such as uniform handling of the couplings, complete decoupling and heavy burden of system optimizer. To overcome the above drawbacks, a serialization-based partial decoupling approach is proposed in this study, which consists of three main steps. First, different disciplines are clustered into some subsystems by analyzing the interdisciplinary sensitivities. Then, for each subsystem, a serialization process is proposed to ensure no coupling loops exist and the subsystem can be solved with no iteration, which can reduce the time cost for solving the disciplinary problem to a large degree. Finally, a local optimization model is constructed for each subsystem to maintain the scale of the global optimizer and ensure mutual independence and parallel processing. The proposed three-layer framework ensures the feasibility of solving for each subsystem and improves the efficiency of optimization execution. Several experiments have been conducted to demonstrate the effectiveness and feasibility of the proposed approach.
Among modern manufacturing methods, lean manufacturing has been a dominant method used in many industrial sectors. The principle of the lean manufacturing is to eliminate the wastes present in various forms of the industry. The adoption of lean manufacturing in an industry could be identified by the leanness measurement through lean assessment. In lean assessment, the evaluator plays a vital role. Selecting the right person for the assessment will reduce the ambiguity, time consumption and computation time. Decision-makers play a vital role in lean assessment. Few studies have been found in the literature to select or identify the decision-maker. In this article, the TOPSIS-Simos method has been proposed to identify a lean resourced employee in the industry. The proposed method is case studied in the manufacturing industries. The lean resourced employee has been identified after computation. The proposed method could be applied to identify the lean resourced employee in all types of manufacturing industries.
Difficulties in the grinding of Ti-6Al-4V originate from the three basic properties: poor thermal conductivity, high chemical reactivity and low volume specific heat of the material. Under severe grinding conditions, all these factors together lead to the accelerated wheel loading and redeposition of chips over the work surface. Redeposition and wheel loading have a significant effect on the surface finish, grinding forces, power consumption and wheel life. In this study, water-based Al2O3 nanofluid as metalworking fluid is applied during the surface grinding of Ti-6Al-4V under minimum quantity lubrication mode after dressing the wheel with different dressing overlap ratios. The severity of the redeposition over the work surface was observed by measuring various surface profiles taken perpendicular to the grinding direction at several locations on the ground surface. The nanofluid application was able to prevent redeposition over work surface that became evident from the measured surface finish parameters that results along the grinding direction. Coefficient of friction was estimated On-Machine using the measured forces for different wheel work speed ratios, depth of cut and dressing overlap ratios. The results showed the effectiveness of nanofluid in reducing friction at high material removal rate (i.e. high depth of cut and high speed ratio) conditions when compared to the dry environment. From the measured forces variation with respect to the number of passes, it became evident that, nanofluid application delayed the frequency of wheel loading and grit fracturing cycle, which leads to the increase in the wheel life.
In production engineering, monitoring of the grinding process is critical for acquiring information on material removal, wheel performance and workpiece quality. Here, a general model of the power signal and material removal rate is proposed to monitor the internal plunge grinding of a bearing outer race way product. Three continuous grinding cycles after dressing were used to analyse the roughing, semi-finishing, finishing and spark-out process under the same parameters. Based on the actual grinding process, a practical analysis method is applied to improve the general model to more accurately predict the power curve. Finally, estimations of grinding wheel performance and grind quality using the grinding power signal model coefficients are also presented. The experimental results showed that the improved power signal model is capable of solving the industrial problem of multi-stage infeed grinding cycles and improving grind quality.
Three different microstructures, namely ferrite–pearlite, tempered martensite and ferrite–bainite–martensite of 38MnSiVS5 microalloyed steel, were produced using controlled thermomechanical processing. The properties are comparable to quenched and tempered steel. The developed microstructures were turned to evaluate their machinability. Mixed modes of response were observed while ferrite–bainite–martensite microstructure exhibits better machinability by way of good surface texture/finish, the ferrite–pearlite microstructure of least strength encounters smaller cutting force.
The Arctic region is expected to play an extremely prominent role in the future of the oil and gas industry as growing demand for natural resources leads to greater exploitation of a region that holds about 25% of the world’s oil and gas reserves. It has become clear that ensuring the necessary reliability of Arctic industrial structures is highly dependent on the welding processes used and the materials employed. The main challenge for welding in Arctic conditions is prevention of the formation of brittle fractures in the weld and base material. One mitigating solution to obtain sufficiently low-transition temperatures of the weld is use of a suitable welding process with properly selected parameters. This work provides a comprehensive review with experimental study of modified submerged arc welding processes used for Arctic applications, such as narrow gap welding, multi-wire welding, and welding with metal powder additions. Case studies covered in this article describe welding of Arctic steels such as X70 12.7-mm plate by multi-wire welding technique. Advanced submerged arc welding processes are compared in terms of deposition rate and welding process operational parameters, and the advantages and disadvantages of each process with respect to low-temperature environment applications are listed. This article contributes to the field by presenting a comprehensive state-of-the-art review and case studies of the most common submerged arc welding high deposition modifications. Each modification is reviewed in detail, facilitating understanding and assisting in correct selection of appropriate welding processes and process parameters.
This study focused on the effect of drilling parameters such as helix angle, spindle speed and feed rate on surface roughness, flank wear and acceleration of drill vibration velocity. Using design of experiments, 18 experiments were conducted on AISI 304 steel with carbide twist drill bits. A laser Doppler vibrometer was used for online acquisition of cutter vibration data in the form of acousto optic emission signals. A fast Fourier transformer was used to convert the time domain signals into frequency domain. Response surface methodology was used to identify significant parameters in the analysis of surface roughness, flank wear and acceleration of drill vibration velocity. A multi response surface optimization technique was used to find out optimum drilling parameters. Helix angle of 25°, feed rate of 10 mm and spindle speed of 750 r/min were found to be optimum cutting parameters for minimization of surface roughness, flank wear and acceleration of vibration velocity.
In order to realize the machining of elliptical holes, the article researches control simulation of shaft center movement orbit using Eulerian method. A new hydrostatic bearing and a hydraulic control system are proposed, and quantitative relation between the expected shaft center coordinates and spool displacement of electro-hydraulic servo valve is studied. With the Eulerian method, open-loop control orbit of shaft center is simulated. And the simulation results indicate that open-loop control method not only controls shaft center movement to form ellipse orbits but also has strong robustness against dynamic disturbing force or instantaneous static disturbing force. This article lays theoretical basis for machining of elliptical holes.
Most recent studies on machining parameter optimization in machining operations focused on reducing machining cost and energy consumption. However, environmental impacts caused by manufacturing activities were not involved in those studies, which can be quantified by equivalent carbon dioxide emissions. In this study, a direct method was proposed to quantify the carbon emissions generated during multi-pass turning operations. Moreover, machining parameter optimization models of multi-pass turning operations in dry and wet cut environments were established using an experimental design method. Three objectives were considered in both models: carbon emissions, operation time, and machining cost. Furthermore, a multi-objective teaching–learning-based optimization algorithm was used to deal with the models. The optimization results indicated that the use of cutting fluids could significantly reduce carbon emissions and machining cost and improve production efficiency in multi-pass turning operations.
In aerospace industry, the materials constituting aircraft evolved considerably in recent decades. The choice of composite materials (carbon fiber–reinforced plastic or multi-material) reduces the weight of structures, but for critical parts that support important forces or temperature, the indicated materials are alloys based on nickel or titanium. Consumption of titanium for the aerospace industry is growing rapidly, and the new generations of aircraft show an increase in the percentage of titanium. The TA6V is mostly used for structural parts, especially for engine pylon. Due to its low thermal properties, it shows a poor machinability, leading tools to undergo severe wears. The aim of this work is to understand the relation between cutting conditions and chamfered tool geometries on chip formation and tool wear. Based on a model dedicated to the understanding of cutting process with chamfered tool and on experimental tests, this work will show the influence of feed, cutting speed, chamfer length and rake angle on tool–chip contact lengths. It will also show the influence of these parameters on the variability of these contacts within a same geometry or cutting condition. This will lead to another interpretation of tool wears and pressures on the rake face.
Fluid jet polishing is an emerging process which possesses the advantages of localized force and less heat generation, as well as the stable and controllable material removal function without tool wear. Due to the complex machining mechanism, it is still difficult to model the material removal rate and predict the surface generation for fluid jet polishing. In this article, theoretical and experimental investigation of three-dimensional-structured surface generation by fluid jet polishing has been carried out. A surface topography simulation model is established for predicting the three-dimensional-structured surface generation by fluid jet polishing. A series of polishing experiments have been conducted to optimize the process parameters of fluid jet polishing and the fabrication of three-dimensional-structured surfaces. In terms of the pattern of three-dimensional-structured surfaces generated, the simulation results are found to agree with the experimental results.
Cell formation is the fundamental step while designing a cellular manufacturing system. Integration of job sequencing with cell formation can attain lower make-spans. The traditional cell formation and scheduling problems consider performance indicators such as productivity, time and flexibility in cellular manufacturing system; however, energy consumption has not been given due attention. Therefore, this research addressed the minimization of total energy consumption by implementing an energy-efficient schedule at the cell formation stage of cellular manufacturing system. For this purpose, a two-phase approach is proposed; in phase I, formation of independent cells is being carried out by considering energy-efficient routings and genetic algorithm is used for improving search performance. In phase II, a formulation is being developed to compute the total energy of the system based on optimal job sequence with respect to minimum idle running of the machines in each independent cell. For the proposed approach, a code is being developed in MATLAB software. Different sample problems have been evaluated. The results showed that the proposed approach is effective in generating independent cells and sequences with minimum energy consumption and make-span.
The 080A15 and 30CrMnMo steels were cut by precision sawing machine. The microscopic characteristic of the chip surface and the chip failure microscopic mechanism have been studied. The studies show that the formation of saw-tooth chip is mainly a function of the strength and thermal conductivity. For 080A15 steel, the strength is low and the thermal conductivity is high, the plastic work was absorbed continuously by the process of plastic deformation, and the heat was dissipated at any moment. The heat energy did not reach the critical value causing thermal softening. The chip is more prone to ductile fracture. For 30CrMnMo steel, the bonding ability is stronger among atoms, and thermal conductivity is smaller. The plastic deformation is extremely fast and the instantaneous temperature rise was very high because the heat energy reached the critical value causing thermal softening. Therefore, the chip is more prone to adiabatic shear failure to form the saw-tooth chip divided uniformly by adiabatic shear band. The research results help to provide the basis for selecting materials with different adiabatic shearing sensitivities in the process of high-speed cutting by studying the energy barrier on the influence of chip failure mechanism.
The three main pillars of sustainability are the society, the environment, and the economy (people, planet, and profit). The key drivers that sustain these three pillars are energy and resource efficiency, a clean and ‘green’ environment that incorporates effective waste reduction and management, and finally cost-effective production. Sustainable manufacturing implies technologies and/or techniques that target these key drivers during product manufacture. Because of the effort and costs involved in the machining of titanium and its alloys, there is significant scope for improved sustainable manufacturing of these materials. Titanium and its alloys are extensively used for specialized applications in aerospace, medical, and general industry because of their superior strength-to-weight ratio and corrosion resistance. They are, however, generally regarded as difficult-to-machine materials. This article presents an overview of previous and current work and trends as regards to sustainable machining of titanium and its alloys. This article focuses on reviewing previous work to improve the sustainable machining of titanium and its alloys with specific reference to the selection of optimum machining conditions, effect of tool materials and geometry, implementing advanced lubrication and/or cooling techniques, and employing advanced and hybrid machining strategies. The main motivation is to present an overview of the current state of the art to discuss the challenges and to suggest economic and environment-friendly ways for improving the machinability of titanium and its alloys.
Surface roughness is one of the most important requirements of the finished products in machining process. The determination of optimal cutting parameters is very important to minimize the surface roughness of a product. This article describes the development process of a surface roughness model in high-speed ball-end milling using response surface methodology based on design of experiment. Composite desirability function and teaching-learning-based optimization algorithm have been used for determining optimal cutting process parameters. The experiments have been planned and conducted using rotatable central composite design under dry condition. Mathematical model for surface roughness has been developed in terms of cutting speed, feed per tooth, axial depth of cut and radial depth of cut as the cutting process parameters. Analysis of variance has been performed for analysing the effect of cutting parameters on surface roughness. A second-order full quadratic model is used for mathematical modelling. The analysis of the results shows that the developed model is adequate enough and good to be accepted. Analysis of variance for the individual terms revealed that surface roughness is mostly affected by the cutting speed with a percentage contribution of 47.18% followed by axial depth of cut by 10.83%. The optimum values of cutting process parameters obtained through teaching-learning-based optimization are feed per tooth (fz) = 0.06 mm, axial depth of cut (Ap) = 0.74 mm, cutting speed (Vc) = 145.8 m/min, and radial depth of cut (Ae) = 0.38 mm. The optimum value of surface roughness at the optimum parametric setting is 1.11 µm and has been validated by confirmation experiments.
Assembly sequence planning is a critical step of assembly planning in product digital manufacturing. It is a combinational optimization problem with strong constraints. Many studies devoted to propose intelligent algorithms for efficiently finding a good assembly sequence to reduce the manufacturing time and cost. Considering the unfavorable effects of penalty function in the traditional algorithms, a new discrete firefly algorithm is proposed based on a double-population search mechanism for the assembly sequence planning problem. The mechanism can guarantee the population diversity and enhance the local and global search capabilities by using the parallel evolution of feasible and infeasible solutions. All parts composed of the assembly are assigned as the firefly positions, and the corresponding movement direction and distance of each firefly are defined using vector operations. Three common objectives, including assembly stability, assembly polymerization and change number of assembly direction, are taken into account in the fitness function. The proposed approach is successfully applied in a real-world assembly sequence planning case. The sizes of feasible and infeasible populations are adequately discussed and compared, of which the optimal size combination is used for initializing the firefly algorithm. The application results validate the feasibility and effectiveness of the discrete double-population firefly algorithm for solving assembly sequence planning problem.
This article proposes the sine series representation of jerk profile for acceleration/deceleration feedrate scheduling of parametric interpolator used in computer numerical control machining tools. By selecting the geometric sequence as the coefficients of the sine series, the closed-form expressions of the feedrate, acceleration and jerk profiles are obtained. The resulting feedrate profile is more concise compared with the polynomial profile and more efficient compared with the trigonometric profile. It can be well accepted by the conventional acceleration/deceleration feedrate scheduling algorithms. Also, an approach is proposed to determine the optimal geometric sequence that makes the tracking time as small as possible. Simulations and experiments of tracking complex contours expressed as free-form non-uniform rational B-spline curves are conducted. The results demonstrate the effectiveness of the proposed feedrate profile and the resulting feedrate scheduling strategy.
Taguchi’s L9 orthogonal array has been effectively used to study the effect of process parameters such as voltage, feed rate and electrolyte concentration on material removal rate in context of two different types of electrolyte, namely, aqueous NaCl solution and CuSO4 mixed aqueous NaCl solution. The results indicated that Cu2+ ions formed due to electrochemical reactions prevent the oxidation of Fe2+ to Fe3+ and catalyze the anodic dissolution of iron during machining. The experimental results were analyzed using analysis of variance method to investigate the significance and percentage contribution of individual process parameters on performance characteristics.
Damage due to delamination is an important issue during drilling in glass-fiber-reinforced plastic composite laminates. Feed-rate during drilling is the most critical parameter. High feed-rate during drilling results in high thrust force on the composite laminate. In this work, dynamics of drilling in glass-fiber-reinforced plastic composite laminates are captured in the form of third-order state-space model between thrust force and feed-rate. Optimal control is then used to control the thrust force generated during drilling. Research has revealed that there is a critical limit on thrust force during drilling in composite laminate below which no delamination occurs. This critical thrust force profile is used in this work as reference in the optimal controller to ensure delamination-free drilling. Present controller precisely tracks the given critical thrust force reference profile and gives optimal feed-rate profile. The glass-fiber-reinforced plastic composite laminate is then drilled at this optimal feed-rate profile to obtain delamination-free holes. Delamination around the holes is quantified in the form of a delamination factor. Experimental results show that the control strategy is efficient and effective in preventing drilling-induced delamination in glass-fiber-reinforced plastic composite laminates.
In manufacturing industries, WC–Co composite material is highly demanded due to its excellent properties such as toughness with hardness, good dimensional stability, and higher mechanical strength. However, the difficulties in its machining restrict the application and competitiveness of this material. This investigation is aimed at studying the impact of different experimental conditions (by varying cobalt content, thickness of workpiece, tool geometry, tool material, abrasive grit size, and power rating) on responses of interest (cutting ratio, overcut, and taper angle) in ultrasonic drilling of WC–Co composite material. The experiments have been planned using Taguchi’s L-36 orthogonal array, and analytic hierarchy process–based technique for order preference by similarity to ideal solution has been applied for optimization of multiple responses. Analysis of variance is also employed to identify the significant factors and the optimized process settings for the different responses. The experimental results showed that abrasive grit size and power rating are most influential for cutting ratio, overcut, and taper angle.
Sustainability assessment is becoming an unquestionable issue for manufacturing companies that are urged by governments and customers to provide environment-friendly products. Machining, as one of the major manufacturing operations, has high potential factors regarding the environmental impacts of production system. Nevertheless, environmental assessments are mainly done post-product design and post-machining processes design. Integrating environmental assessment in the machining processes design could lead to significant improvements in sustainable manufacturing field. Major difficulties to perform such an assessment are the availability of the machining data and the lack of calculation rules to express them in terms of environmental impacts. This article presents a new approach based on the STandard for the Exchange of Product model data—compliant Numerical Control to integrate the machining environmental assessment in the earlier design phases. It proposes to establish cognitive links between the machining data included in STandard for the Exchange of Product model data—compliant Numerical Control and environmental indicators. The approach is implemented on a demonstrator and validated by a use case.
The integration of process planning and scheduling is a very important problem because it proposes a new idea for improving the performance of a manufacturing system. At present, most existing studies on this problem are static, which assumes that all the jobs to be processed are available in the beginning. However, the practical processing situation is dynamic, such as new job arrivals. Since dynamic production situations are different with static cases, it is important to study the characteristics of actual production situations. In this article, the characteristics of dynamic integrated process planning and scheduling problem with job arrivals are studied. A novel mixed integer linear programming model is established to accommodate new job arrivals, and three criteria (makespan, stability, and tardiness) are considered. New periodic and event-driven rescheduling strategies are presented. In the proposed strategy, newly added jobs together with uncompleted jobs will be rescheduled by non-dominated sorting genetic algorithm-II to obtain the optimal Pareto front when the rescheduling procedure is triggered. The entropy-based weight assigning method together with the Technique for Order of Preference by Similarity to Ideal Solution method is adopted to determine an appropriate schedule among the resultant non-dominated solutions. A set of well-known benchmark instances is employed to investigate the characteristics of the dynamic integrated process planning and scheduling problem with random job arrivals. Experimental results show that the length of a scheduling interval, the number of newly added jobs, and the shop utilization have an important influence on the efficiency of a manufacturing system.
Self-excited vibrations of the face milling process can result in instability, poor surface finish and machine tool failure. In order to avoid chatter vibrations, this article develops an algorithm for predicting the stability lobes for face milling processes. It considers the factors including radial instantaneous chip thickness, entry and exit angles and the dynamic interaction between cutting tool and workpiece which is often neglected by many researchers. An electronic impact hammer is used to identify the dynamic parameters of the face milling system. Milling experiments have been conducted to validate the predictive capability of the developed algorithm for stability lobes. The results show that the prediction model can estimate the stable and unstable zones for face milling process. This article provides a frequency-domain method for establishing stability lobes which can predict stability zones rapidly. The outcome of this research will bring about methodologies for cost-effective monitoring of face milling processes and maximize the material removal rate.
Unlike previous studies that have revealed a link between quality improvement programs and organizational culture typologies in individual companies, this study describes organizational culture dimensions that affect the use of quality improvement tools and methodologies and how both affect supply chain company performance. Structural equation modeling methods are applied to a sample of 200 organizations in the supply chain of a Canadian multinational company. The results show that employee promotion and investment constitutes the most influential cultural dimension. Organizational objectives and an employee reward system individually affect Kaizen. When the level of formalization in an organization is high, Kaizen and total quality management tools are used more intensively. When the level of formalization is low, lean manufacturing and internal audits are used more intensively. Superior communication in an organization causes plan–do–check–act approaches, lean manufacturing methods, corrective actions and internal audits to be used less intensively. Generally speaking, most quality improvement tools and methodologies positively influence business performance. These results suggest that organizations can improve business performance levels by selecting appropriate quality improvement programs depending on existing organizational culture dimensions and may thereby develop an organizational culture that enables successful quality improvements in a supply chain context.
Heavy machine tool work under such high-load conditions that chatter vibrations are prone to occur, which significantly diminishes the machining efficiency and quality. Stability lobe diagrams are commonly used to select appropriate spindle speed and axial depth of cut to get rid of chatter and maximize the material removal rate. However, this needs precise identification of the dynamics of the entire machine tool structure, especially in the low-frequency range. Operational modal analysis has been the proven technique for estimating dynamic characteristics of machine tool structures in operation conditions. In this article, a complete methodology was presented for employing operational modal analysis for heavy machine tool in machining conditions. A random cutting exciting method originally presented by Minis is modified which generates pseudorandom impulse force to excite a heavy vertical lathe structure. And the excitation signal of random cutting force was modeled to analyze the effect of cutting parameters on energy and frequency band of the excitation. One operational modal analysis method, the pLSCF (referred to as PolyMAX) method, was employed to estimate modal parameters during machining. It was also observed in chatter tests that the operational modal analysis results are more accurate than the traditional impact test results in characterizing the dynamics of machine tool structure in machining.
This article reports a follow-up research to investigate further the component technologies of a cost-effective manufacturing route designed to achieve function and length scale integration in products. The route employs a viable master-making process chain that integrates compatible and at the same time complementary, structuring and replication technologies to fabricate Zr-based bulk metallic glass inserts. To validate them, they are subsequently integrated into a micro-injection moulding machine, and polymer structures incorporating both micro- and nano-scale features are replicated. Especially, the masters and/or replicas after each processing step were analysed and the factors affecting its overall performance were identified. The research demonstrated that the master-making process chain can be a viable fabrication route for both fully amorphous and partially crystalline Zr-based bulk metallic glass inserts that incorporate different length scale features. The results also showed that relatively good fidelity of the different scale features can be achieved with the micro-injection moulding process, and thus, it can enable function and length scale integration in thermoplastic components.
Off-axis aspheric mirror is an important component widely used in optical system and precision measurement instrument. Off-axis parabolic surface is one typical shape of off-axis aspheric mirrors which can enlarge focal length and widen field-of-view. Two typical ultra-precision turning methods which are turning the cylindrical blank by revolving around the axis of parabolic surface (TPS) and revolving around the axis of cylindrical surface (TCS) are analyzed and compared for off-axis parabolic surface in this article. Three-axis (X, Z, C) turning machine is applied and kinematic analyses of two linear axes (X, Z) are studied during cutting with the single point diamond turning. The tool paths are generated and installation errors are analyzed under two different conditions. Primary experiments are conducted to verify the effectiveness of theoretical analyses. The obtained results demonstrate that the surface machined with TPS method has better machining quality than the one machined with TCS method.
A tool condition monitoring system based on support vector machine and differential evolution is proposed in this article. In this system, support vector machine is used to realize the mapping between the extracted features and the tool wear states. At the same time, two important parameters of the support vector machine which are called penalty parameter C and kernel parameter
Dynamics of robot wrist is concerned with the relations between the forces acting on the robot wrist mechanism and the accelerations it produces. Many valuable contributions come forth in recent years, as a suitable dynamics model for a robot wrist is very crucial for analysing its behaviour, on-line control of motions and forces, trajectory design and optimization, and design of robot mechanisms. However, current researches always focus on full-actuated robot wrists. The proposed underactuated robot wrist is a novel mechanism with fewer actuators than the degrees of freedom. As the existing dynamics models for the full-actuated robot wrists are not suitable for the underactuated robot wrist anymore, the dynamics model of the underactuated robot wrist becomes an important issue. This article is devoted to a model for dynamics analysis of a novel underactuated robot wrist. After this underactuated robot wrist is introduced, the dynamics analysis of the underactuated robot wrist with numerical simulation based on virtual prototyping is proposed in detail. The peak values of servo motor in the joint motion unit are also estimated. The dynamics analysis of a novel underactuated robot wrist is used to demonstrate the proposed method.
A feedback control system for quality characteristics is one of the most crucial components in Taguchi’s on-line quality management. In this article, three problems in Taguchi’s on-line quality feedback control system are discussed. Furthermore, countermeasures for improving the system are proposed. First, the quality loss of products that are out of control is reestimated by approximating the probability density of their quality characteristic value to a linear distribution. Second, the quality loss of products that are under control is reestimated by approximating the probability density of their quality characteristic value to a normal distribution. Third, the decreased profit resulting from a process shutdown, which is excluded in Taguchi’s on-line quality feedback control system, is considered in calculating the adjustment cost. The management cost and quality loss constitute the total quality cost. In the improved on-line quality feedback control system, the optimal measurement interval and optimal administrative boundary are calculated by minimizing the total quality cost using an iterative method. An example of the adjustment of the administrative boundary and the measurement interval for manufacturing automobile parts is presented to illustrate the effectiveness of the improved on-line system.
With the development of multi-directional forging technology, heavy multi-directional forging press has been widely used in manufacturing industry. However, there is a contradiction between the independence of structure and the independence of mechanics, which becomes a bottleneck and limits the development of heavy multi-directional forging press tonnage. For the contradiction, a novel pre-stressed wire-wound orthogonal preload frame structure is proposed in this article to solve the problem, and the stiffness and deformation characteristic of pre-stressed wire-wound orthogonal preload frame structure under three loading states (vertical–horizontal loading, vertical loading and horizontal loading) are analyzed by finite element analysis and the 1:10 model experiment of 400-MN multi-directional forging press whose loading tonnage in the horizontal direction is the largest tonnage in the world. The results show that pre-stressed wire-wound orthogonal preload frame structure has advantages in large stiffness, high strength and excellent integrity under a reasonable preload coefficient. Furthermore, pre-stressed wire-wound orthogonal preload frame structure can satisfy the design requirement for carrying frame of heavy multi-directional forging press and may promote the development of multi-directional forging technology and related equipment industry.
Manufacturing systems involve a huge number of combinatorial problems that must be optimized in an efficient way. One of these problems is related to task scheduling problems. These problems are NP-hard, so most of the complete techniques are not able to obtain an optimal solution in an efficient way. Furthermore, most of real manufacturing problems are dynamic, so the main objective is not only to obtain an optimized solution in terms of makespan, tardiness, and so on but also to obtain a solution able to absorb minor incidences/disruptions presented in any daily process. Most of these industries are also focused on improving the energy efficiency of their industrial processes. In this article, we propose a knowledge-based model to analyse previous incidences occurred in the machines with the aim of modelling the problem to obtain robust and energy-aware solutions. The resultant model (called dual model) will protect the more dynamic and disrupted tasks by assigning buffer times. These buffers will be used to absorb incidences during execution and to reduce the machine rate to minimize energy consumption. This model is solved by a memetic algorithm which combines a genetic algorithm with a local search to obtain robust and energy-aware solutions able to absorb further disruptions. The proposed dual model has been proven to be efficient in terms of energy consumption, robustness and stability in different and well-known benchmarks.
In this study, material removal rate (MRR) and surface roughness (Ra) in electrical discharge machining process have been modeled to make the process more efficient and reliable. First, adaptive neuro fuzzy inference system as one of the most used methods has been applied for prediction of material removal rate and Ra. Also a proposed method, that is, nonlinear modeling by system identification, has been applied to predict material removal rate and Ra. A group of electrical discharge machining experiments considering four input variables was conducted to collect dataset for training the predictive models. At the end, the comparison of predicted results from both approaches with experimental data shows that the new method has a much better performance than the adaptive neuro fuzzy inference system approach.
Pressure-assisted forming of tubes allows producing a wide variety of tubular components that are difficult or impossible to fabricate by means of conventional tube forming. In contrast to previous investigations in the field that were almost exclusively focused on the utilization of fluids (tube hydroforming) or elastomers (tube rubber forming) as pressuring medium, the subject matter of this article is centred in the utilization of low melting point, recyclable, metallic alloys as solid pressurizing medium. The aims and scope of the article are centred on the feasibility of forming straight carbon steel tubes into complex gooseneck geometries with non-concentric cross sections using lead as a solid pressuring medium and employing a double-action cam-driven tool system. The presentation is focused on the tool system, on its adequacy to produce customized tubular components, on the required forming forces and on the typical modes of deformation that result from the different movements provided by the vertical and horizontal actuators of the double-action tool system. Results and observations confirm that the utilization of a double-action tool system with a solid pressurizing medium to assist plastic deformation and prevent collapse can be successfully and effectively employed to fabricate non-concentric tubular cross sections for prototypes and small batches of lightweight components.
This article presents a derivation of the stiffness matrix of a general redundantly actuated parallel mechanism based on the overall Jacobian. The Jacobian of the constraints and actuations is derived using reciprocal screw theory. Based on the mapping relationship between constraint, actuated and external forces combined with the principle of virtual work, a compatibility equation for the deformation of all of the limbs is achieved, and the stiffness model of the general redundantly actuated parallel mechanism is derived. The 5-UPS/PRPU redundantly actuated parallel machine tool is used to illustrate this method. The parallel machine tool comprehensively reveals the effect of the elastic deformation of active–passive joints and some basic transmission parts. The stiffness model is further validated by experimental data. Moreover, the global stiffness matrix of the general redundantly actuated parallel mechanism can be separated into two parts via matrix decomposition. The first part is the stiffness matrix of the corresponding non-redundant parallel mechanism, and the second part is the stiffness matrix of the redundantly actuated limbs (actuators). The redundantly actuated 5-UPS/PRPU parallel machine tool is also investigated for further analysis. The different stiffness characteristics of the machine tool and its corresponding non-redundant 5-UPS/PRPU parallel machine tool are compared. Actuation redundancy is found to improve the stiffness performance of the machine tool efficiently.
Manufacturing processes are among the most energy intensive on earth. As negative ecological and economic impacts increase, reducing energy consumption is becoming critically important. In this article, a comprehensive overview of energy-saving strategies and opportunities for increasing energy efficiency in manufacturing operations is presented, with a focus on metal cutting processes. The issues and approaches involved in energy efficiency of machine tools and machining operations are reported in the literature and a structured research methodology is proposed for this purpose including prediction and modelling of machine energy consumption, determining the relationship between process energy consumption and process variables for material removal processes and optimization of cutting parameters in order to reduce energy consumption. Numerous techniques for increasing energy efficiency in manufacturing processes are identified and summarized, strengths and weaknesses of previous studies are discussed and potential avenues for future research are suggested.
In laser-induced thermal-crack propagation, thermal stresses control the crack propagation mode and the quality of the crack surface. In this article, the 1064-nm semiconductor laser as a volumetric heat source is used for symmetry and asymmetry cutting glass. One of the problems in laser asymmetry linear cutting glass with laser-induced thermal-crack propagation is the quality of the crack surface which gets worse than that in symmetry cutting. This study lays great emphasis on analyzing the effect of the focus position and shear stresses on the crack sectional shape in semiconductor laser asymmetry linear cutting glass. This article indicates the volumetric heat flux formula, which simulates the temperature distribution from the material above or below the focal point. The heat source should be positioned above the focal point. Optical microscope photographs of the crack surface and sectional shape are obtained to examine the surface quality which is explained from the results of the stress fields using the extended finite element method simulation. In asymmetry cutting, shear stress is parallel to the crack surface and perpendicular to the cutting direction, which makes the crack surface smooth but uneven.
A numerical model based on computational fluid dynamics is developed to analyze fluid flow and thermal aspects in grinding. The model uses multiphase fluid flow with heat transfer based on the volume-of-fluid method, convection, conduction in solids and a multiple reference frame model of the porous grinding zone. Fluid velocity vectors, useful flow rate, grinding temperatures and energy partition are predicted using the model. In lieu of direct measurements of these quantities, the verification relies on the indirect assessment of surface integrity. The simulation results provide adequate agreement with the measured residual stress, depth of heat-affected zone and full width at half maximum profile with respect to the grinding temperatures.
In order to improve the performance of the cutting tool, third-generation tools with multi-layered nanocoatings on the rake face are used. During machining, the chip–tool interactions depict that although the tool wear on the rake face is located in the close proximity of the cutting edge, that is, within 800 µm, all the commercially available cutting tools have the coatings on the entire rake face. Taking into account the tribological properties required by the rake face close to the cutting edge, that is, high wear resistance and low friction, this study makes an attempt to identify, characterize and locate the actual wear zones/regions in terms of hard and soft zones in the chip contact area of tungsten carbide (WC) inserts close to the cutting edge in turning. Mamdani fuzzy inference system model was developed, trained with the sample experimental data and tested with the test data. The simulated results showed that the average error values of edge chipping (in X- and Y-directions), nose damage and crater wear (in X- and Y-directions) are about 2.37%, 3.01%, 2.86%, 2.66% and 1.89%, respectively. The fuzzy model developed in this study showed remarkable prediction of the wear zone locations and is also helpful for the researchers to decide the type of coating (hard and soft) along the specified zones for reducing the cost of production.
Waviness error is one of the most critical errors in the large aspheric lenses grinding and one that has a strong impact on the performance of the optical system. In this article, the waviness error of large axisymmetric aspheric lenses for X-axis direction as well as Z-axis direction is analyzed by employing grate parallel grinding method. The grinding wheel vibration and Z-axis interpolation pace are regarded as the main causes of the surface waviness error. Furthermore, to reduce the waviness error, the influence of grinding parameters on waviness error is investigated. The waviness errors measured during grinding experiments are in good agreement with the theoretical results and the appropriate grinding parameters are recommended.
Most of commercial CAM software solutions (SolidCAM, Unigraphics and etc.) are commonly employed for generating tool paths on machining of freeform surfaces. However, these CAM software solutions are presently unable to support fast tool/slow slide servo diamond turning of freeform surface due to difference in coordinating systems. In contrast to traditional machining processes, fast tool/slow slide servo diamond turning is controlled by both linear and angular positions of the workpiece and is known as polar or cylindrical coordinate system. Hence, a special CAM post-processor is required to generate the spiral tool trajectory in fast tool/slow slide servo diamond turning. However, these special CAM software solutions are very expensive. Manufacturers have been searching for solutions to sustain their competitive advantage in mass producing products at the shortest time to market and at a most economical cost. Hence, these drive the needs for an alternative and economical option of generating accurate tool trajectory for fast tool/slow slide servo diamond turning of freeform surfaces. This article proposes an attractive solution with an integration of Visual Basic application programming interface into SolidWorks to generate spiral tool trajectory for diamond turning of freeform surface. In this proposed methodology, the spiral tool trajectory can be extracted directly from computer-aided design models of freeform surface without utilizing any expensive CAM software. In addition, the critical cutting parameters and tool geometrical angles were also optimized with the developed methodologies for the accurate machining of freeform surfaces in the hybrid fast tool/slow slide servo process.
The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. However, the focus of existing works is mainly on deterministic constraints of jobs. This article proposes a novel memetic algorithm for the integrated process planning and scheduling problem with processing time uncertainty based on processing time scenarios. First, a mathematical model for the stochastic integrated process planning and scheduling problem based on the network graph is established. Due to the nonlinearity in the model and the complexity of the problem, a memetic algorithm is then suggested for this problem. A novel local search (variable neighborhood search) algorithm is incorporated into the memetic algorithm. Two effective neighborhood structures are employed in the variable neighborhood search algorithm to improve the overall performance of the population. Furthermore, for the uncertainty in processing times, a set of scenarios have been generated to evaluate each individual. Finally, two performance measures—the expected performance measure and the worst-case deviation measure—are introduced and compared. In the experimental studies, the proposed memetic algorithm is tested on typical benchmark instances. Computational results show that the expected makespan measure performs better than the worst-case deviation measure and the proposed method exhibits high performance especially for large-scale instances. In addition, the results obtained by the proposed memetic algorithm are more satisfactory than those obtained by the algorithm that considers deterministic processing times only.
Reduction in the dimensional error of an assembly mostly focuses on the variation of fixtures and parts inside, in which the variation is mainly controlled by the methods relating to the fixture design and variation analysis. Recently, more researches concentrate on the dimensional analysis of the aluminum assembly where the distortion of rivet joints cannot be neglected, that is, the riveting-induced dimensional error. Hence, both the device design and the variation analysis for the riveting are drawing much attention to reduce the overall distortion. This article presents a dimensional reduction method, a rivet upsetting direction optimization based on a local-to-global dimensional calculation. The method is developed from a recent framework of assembly process optimization according to the discovered sensitivity between global dimensional error and rivet upsetting directions. A potential function that gathers the overall effect of every locating error is included. Simulations for three riveted assemblies are presented for comparison and results show that the method is efficient for the specific assignment of every rivet upsetting directions, and the effects of locating errors and rivet upsetting directions are highly coupled. The coupled effect yields the key questions in the improvement of this method. Detailed suggestions are then summarized.
Carbon fiber–reinforced plastics have been widely applied in aerospace industry as aircraft structural components due to their excellent mechanical and physical properties. The countersinking process of the carbon fiber–reinforced plastic hole is indispensable for the assembly of countersunk head screw. In conventional countersinking process of carbon fiber–reinforced plastics, it is prone to produce the delamination, fiber pullout, poor surface levelness and dimensional accuracy of countersunk hole. As a new technology, the rotary ultrasonic elliptical machining for countersinking of carbon fiber–reinforced plastics is employed, which is a non-traditional process that can effectively improve the surface levelness, surface integrity and machining accuracy of carbon fiber–reinforced plastic countersunk hole. This article reported a feasibility study on the rotary ultrasonic elliptical machining for countersinking of carbon fiber–reinforced plastics without coolant for the first time. The processing principle of rotary ultrasonic elliptical machining for countersinking was illustrated according to the countersinking models and the equations of motion locus. Based on the principle analysis, the surface levelness, tool blades’ path and countersunk hole surface morphology in rotary ultrasonic elliptical machining of the separated and unseparated types were analyzed compared to that in conventional countersinking. In addition, the rotary ultrasonic elliptical vibration transducer was designed and fabricated, as well as the experimental platform was set up. The experimental results demonstrated that the rotary ultrasonic elliptical machining achieved much better results than that in conventional countersinking, such as lower thrust force, torque, cutting temperature, better surface levelness, hole dimensional accuracy, surface integrity and chip-removal effect. The experimental results also verified the feasibility of rotary ultrasonic elliptical machining for countersinking of carbon fiber–reinforced plastics.
The development of various nontraditional principles to finish the internal surfaces and passages is reviewed. In particular, attention is focused on three relatively mature finishing techniques: abrasive flow machining, internal magnetic abrasive finishing and fluidized bed machining. Their working principles, capabilities and limitations are evaluated accordingly. Finally, the significance of developing internal surface finishing capabilities and the vast potential ahead of this research field are highlighted.
The machining systems that mainly consist of machine tools are numerous and are used in a wide range in industries. The total amount of energy consumption by machining systems in the world is extremely high. The loading loss energy is one of the most important and complicated parts of the energy consumption of machine tool in machining processes. The key of acquiring the loading loss energy is the acquisition of the loading loss coefficient, which is indispensable for machine tools’ energy efficiency on-line monitoring, energy prediction and energy quota customization. Up to now, the loading loss coefficient is mainly obtained by the experimental method which needs to conduct a large amount of experiments and a comprehensive on-line measurement to obtain the input power, idle power and cutting power beforehand. On the other hand, in many cases, it is unavailable to install the dynamometers on the machine tool’s worktable to measure the parameters on-line. This article provides a mapping method to acquire the loading loss coefficient of main driving system of machine tools. First, choose a standard machine tool, cutter and workpiece to construct the standard machining circumstance. Second, carry out the experiments with a series of given cutting parameters under the standard circumstance and record the cutting power accordingly. Third, construct the overall cutting power model which can be used to calculate the cutting power of any other target machine tools under the standard machining circumstance. Fourth, establish the air-cutting power database of the target machine tools. Then, carry out the experiments on the target machine tool with the parameters which is as close as possible to the standard parameters and record the input power of the main driving system respectively. Finally, substitute the input power, air-cutting power and cutting power into the acquisition model to calculate the loading loss coefficient. The case study indicates that this method with high accuracy, on the other hand, can simplify the procedure of the acquisition of the loading loss coefficient to a great degree and shows that the method is practical and promising.
Several control charts have been constructed to simultaneously monitor the process mean and variability. A single chart is often used instead of two charts to detect shift in the process mean and variability separately. A new single generally weighted moving average control chart is now proposed to monitor the process mean and dispersion simultaneously, based on Taguchi’s loss function. A Monte Carlo simulation is used to calculate average run length to study the performance of this control chart when the process is shifted. A comparison is made with an exponentially weighted moving average control chart in terms of average run lengths. Two examples are also included for showing the practical application of the proposed control chart.
For more than half a century, offshoring has been a trend among many industry sectors and all company sizes which are aiming to expand business by reducing costs and accessing foreign markets. However, in recent years, the evidence indicates that offshoring strategies may no longer continue to provide the same level of benefits for organizations’ manufacturing activities. Companies have begun to establish a better understanding of the total risk/benefit-balance and base their supplier decisions on strategic supply chain issue rather than simply relying on cost analysis. Hence, it is evident that there are tendencies to reverse the offshoring strategy and re-shoring manufacturing activities back to the home country. Despite the significance of this phenomenon to manufacturing, the supply chain literature has focused predominantly on the macro economic analysis, while the literature on the operational aspects of re-shoring is relatively sparse. The first half of this article aims to address the first research question which identifies the operational motivations behind the re-shoring phenomenon. This is done by studying the current literature available on the context of re-shoring. The second half of the article determines the feasibility of a manufacturing strategy, ‘postponement’, as a possible solution for the companies to adjust and cope with the volatile customer demands and new generation of technologies towards more responsive production and customizable products.
Cloud manufacturing offers the potential to make mass manufacturing resources and capabilities more widely integrated and accessible to users through network. Most related research assumes that there exists only one management center for all manufacturing resources and capabilities in a manufacturing cloud. However, this could cause the efficiency problem (e.g. scheduling time) and harm the quality of service (e.g. response time). Actually, a large-scale manufacturing cloud should have multiple management centers to deal with massive, widely distributed manufacturing resources and capabilities and users; meanwhile, the constraint of finite manufacturing resources and capabilities and the cost of remote collaboration should be taken into consideration. Thus, this article first presents the architecture for the multi-centric management with two-level scheduling strategy combining the advantages of the centralized and decentralized decision-making. Then, after quantifying the availability and the collaborative cost of the manufacturing resources and capabilities, we propose a global optimization model for the manufacturing resources and capability allocation under the multi-centric architecture. Finally, a case study adopting our new method shows that the utilization of the manufacturing resources and capabilities would be more balanced, while the cost of the total collaboration would be reduced, compared with the typical decentralized solution. The research results can support cloud manufacturing to effectively deal with the challenge of management and allocation for increasingly large-scale and distributed manufacturing resources and capabilities.
This study presents a thorough literature review on the powder-bed laser additive manufacturing processes such as selective laser melting of Inconel 718 parts. This article first introduces the general aspects of powder-bed laser additive manufacturing and then discusses the unique characteristics and advantages of selective laser melting. The bulk of this study includes extensive discussions of microstructures and mechanical properties, together with the application ranges of Inconel 718 parts fabricated by selective laser melting.
Process monitoring is a major focus on improving productivity of discrete manufacturing. With the recent application of new technologies such as radio frequency identification to manufacturing process, real-time production information has become available for decision support in manufacturing system. This study presents a radio frequency identification–based visibility monitoring rule for tracking work-in-process. Specific to the aviation manufacturing shop floor, a case study for demonstration is designed. The value of radio frequency identification–enabled real-time information is investigated within the discrete manufacturing operation. For this purpose, a simplified simulation model is developed to test the benefit of radio frequency identification–based rule compared to the classical scheduling rule. The results indicate that the adoption of radio frequency identification brings better production performance.
Dynamic compliance of machine tool spindle is a necessary input for stability limit prediction. It can be determined by a single input–single output modal analysis, so called tap test. Despite methodology of modal analysis is well known for many years and there are several commercially available software packages supporting it, executing the experiments and evaluation of the results require both knowledge and skill. Therefore, there is a need for automation of all stages of data acquisition and signal processing to make this method applied in industry. This article presents the methodology, algorithms and software which execute all operations and analysis automatically; thus, they can be done directly on the factory floor without the involvement of highly qualified personnel. It enables completing of the tap test and obtaining proper results by an operator who do not have any knowledge on modal analysis. This article presents examples of the software application in factory floor conditions.
As a common phenomenon, chatter is one of the most important factors that inhibit the improvement of productivity and deteriorate the machined surface quality in milling process. In this article, the mathematical model of the dynamic machining process is first constructed with multi-delays, in which the effect of the cutter’s helix angle on the chatter is considered. And a new integral interpolation method is proposed to predict the stability lobes. Based on this method, the mathematical model which is divided into two parts is calculated respectively with an interpolation method and an integration method. Using the Floquet theory, the stability limits of the dynamic milling system for an arbitrary point can thus be precisely predicted. Subsequently, the convergence rate of this integral interpolation method is analyzed. In order to verify the mathematical model, the stability lobes with uniform and variable cutter pitch angle are computed and the results show a good agreement with published experimental data; also one experiment is conducted to validate the proposed model and the method. Simultaneously, the simulation of a stability lobe with non-zero helix angle is also performed and the results validate the fact that the proposed method is capable of predicting stability limits with high accuracy. Finally, the influences of the cutter and process parameters such as helix angle, pitch angle, down-milling or up-milling and radial cutting depth on the milling chatter are analyzed.
An integrated manufacturing system needs automated conversion of design information into its manufacturing counterpart. This is partly dealt with in the present study for extracting the manufacturing information for computer-aided process planning systems, including the identification of tool approach direction, attributing the dimensional and geometric tolerances to the machining features, and identification of the reference faces. In spite of extensive study conducted on computer-aided process planning systems, further investigation is still needed to develop automation in attributing tolerances to machining features and identifying the reference faces. The authors have proposed new methods to implement these tasks. A detailed case study has been used to illustrate the application of the developed algorithms.
Turn milling is one of the machining processes used to mill circular work pieces while the work piece rotates about its own axis. Orthogonal milling is one of the turn milling processes where the bottom part of cutter removes material from the rotating work piece with high metal removal rate. In this article, tool condition was studied by analyzing surface roughness and vibration of cutter with the use of response surface methodology. According to design of experiments, 16 experiments were conducted on ASTM B139 phosphor bronze with high-speed steel end mill cutter on four-axis milling machine. The response surface methodology was used to find out significant parameters that are affecting surface roughness and amplitude of cutter vibration. A multi-response optimization technique was used to identify optimum cutting parameters for less surface roughness and amplitude of cutter vibration.
Acceptance sampling is a statistical procedure for accepting or rejecting production lots according to the result of a sample inspection. Formalizing the concept of assisted acceptance sampling, this article suggests the use of consolidated tools for reducing the risk of human errors in acceptance sampling activities. To this purpose, the application of augmented reality techniques may represent a profitable and sustainable solution. An augmented reality–based prototype system is described in detail and tested by an experimental plan. The major original contributions of this work are (a) introducing the new paradigm of assisted acceptance sampling and (b) developing a preliminary application in an industrial-like environment. This application is a first step towards the realization of a complete assisted acceptance sampling system.
The optical performance of the off-axis three-mirror imaging system can be greatly improved using freeform surfaces. This article focuses on the polishing of the primary mirror and tertiary mirror in an off-axis three-mirror imaging system. The primary mirror and tertiary mirror are fabricated on one monolithic substrate and described by non-uniform rational B-spline–based freeform surfaces. The separated and integrated polishing strategies are presented for polishing the two mirrors on the four-axis computer numerical control polishing platform. A tool path generation approach is proposed for polishing of the non-uniform rational B-spline–based freeform surface. Three kinds of the tool paths are given for ultra-precision polishing of the primary mirror and tertiary mirror with the freeform surfaces. The concentric circle path and the approximately concentric circle path are generated for polishing two mirrors separately, while the spiral path is calculated for integrated polishing of two mirrors simultaneously. The polishing tool posture along the planned tool paths is also analyzed. The ultra-precision polishing experiments of the primary mirror and tertiary mirror on the four-axis computer numerical control polishing platform are performed to verify the proposed approach for tool path generation.
This study covers new trends and techniques in the field of predictive maintenance, which has been superseding traditional management policies, at least in part. It also presents suggestions for how to implement a predictive maintenance programme in a factory/premise and so on. Predictive maintenance primarily involves foreseeing breakdown of the system to be maintained by detecting early signs of failure in order to make maintenance work more proactive. In addition to the aim of acting before failure, it also aims to attend to any fault, even if there is no immediate danger of failure, to ensure smooth operation and reduce energy consumption. Predictive maintenance has been adopted by various sectors in manufacturing and service industries in order to improve reliability, safety, availability, efficiency and quality as well as to protect the environment. It also has created a separate sector, which specializes in developing predictive maintenance instruments, offering dedicated predictive maintenance solutions and training predictive maintenance experts. Predictive maintenance techniques are closely associated with sensor technologies but for efficient predictive maintenance applications, a comprehensive approach, which integrates sensing with subsequent maintenance activities, is needed to be adapted in accordance with the needs of the particular organization. Recent advances in information, communication and computer technologies, such as Internet of Things and radio-frequency identifications, have been enabling predictive maintenance applications to be more efficient, applicable, affordable, and consequently more common and available for all sorts of industries. Researches on remote maintenance and e-maintenance have been supporting predictive maintenance activities especially in unsafe working environments and scattered locations.
The aim of this research is to monitor and classify the broken chip signals from the dynamic cutting forces, in order to predict the surface roughness during the computer numerical control turning process utilizing the Meyer wavelet transform to decompose the dynamic cutting forces. The dynamic cutting forces of the broken chips and the surface roughness can be decomposed into the different levels. The levels of decomposed cutting forces can aid to explain the broken chip formation and the surface roughness profile in both time and frequency domains. The experimentally obtained results showed that the surface roughness frequency occurs at the higher level of decomposed cutting forces, especially at the fifth level, although the cutting conditions are changed. However, the chip breaking frequency appears at the lower level, which depends on the cutting conditions and the chip length. The ratio of the fifth level of decomposed feed forces to that of main forces is proposed to predict the surface roughness during the in-process cutting. It is understood that the broken chip formation can be separated clearly and the surface roughness can be predicted well during the cutting, regardless of the cutting conditions.
To provide a suitable rotation rate for different machining processes, a single machine tool spindle should work over a wide range of speeds. This study considered the effects of speed on dynamic behaviour of ball bearings and combined the fatigue life model and ball bearing internal load distribution model to determine the appropriate preload. First, the influence of speed on internal load distribution and ball bearing contact angles was analysed. The preload was calculated using a ball bearing internal load distribution model. Next, assuming constant bearing fatigue life, the theoretical preload curves were determined using the fatigue life model by changing the reliability factor. Finally, at low speeds, the maximum designed preload (design value) was set as the initial preload. With the increase in speed, the optimum preload was hierarchically obtained within the internal region between the theoretical preload curves. An experimental test rig for the optimum preload of ball bearings, which can automatically adjust the preload, was developed. The proposed method for determining the optimum preload was verified using the measured performance indicators, including the temperature, motor currents, and vibration of ball bearings. The results showed that the optimum preload suggestion made the test ball bearings exhibit excellent behaviour.
The characteristic curve of the envelope generated by the tool motions is an important medium for measuring the distance between the tool and the desired surface. Via the single parametric surface envelope theory in differential geometry, this article proved the correctness of the characteristic curve obtained by minimum distance pairs. Simultaneously, combined with the existing envelope theory and the longitude method, an algorithm based on a velocity field is proposed to approach the characteristic curve. The torus cutter is first dispersed into longitudes and then the characteristic point on each longitude is determined with the estimated velocity. In the experiments, the actual velocity of the estimated characteristic point is computed by the true trajectory simulation of the tool. Therefore, the deviation of the proposed method could be measured comparing with the actual velocity. In the implementations, the proposed method is validated in machining a flat, a spiral, and a blade surfaces. In machining the spiral, our algorithm improves approximately 7 times accuracy with 1/7 time cost compared with the existing methods. The results in the blade surface example prove the stableness of the proposed algorithm.
Increasing energy consumption of manufacturing industry demands novel approaches to achieve energy conservation and emission reduction. Most of the previous research efforts in this area focused more on analyzing manufacturing energy consumption of a process or that of a machine tool with less concern on the system level of advanced machining workshop, especially a flexible manufacturing system. In this article, a new energy-saving approach of flexible manufacturing system is put forward based on energy evaluation model for integration of process planning and scheduling problem in flexible manufacturing system (flexible manufacturing system-integration of process planning and scheduling). First, complying with feature precedence and other technological requirements, flexible manufacturing system -integration of process planning and scheduling is mapped as an asymmetric traveling salesman problem of which operations are provinces and candidate operations are cities belonging to different provinces. To evaluate the performance of each solution of the asymmetric traveling salesman problem, energy consumption evaluation criteria for flexible manufacturing system-integration of process planning and scheduling are established and three energy efficiency indicators are also provided to perform further analysis on manufacturing energy consumption, that is, part energy efficiency, machine tool energy efficiency and feasible solution energy efficiency. Then, a mutation-combined ant colony optimization algorithm is proposed to solve the flexible manufacturing system-integration of process planning and scheduling which combined roulette and mutation selection methods to pick out the next candidate operation. The pheromone trails associated with edges are released by the so-far-best ant or the iteration-best ant probabilistically to both keep the search directed and avoid converging to the local best. Finally, a case study of flexible manufacturing system in advanced machining workshop is employed to demonstrate the feasibility and applicability of this approach in three different scenarios and compared with the "process planning then scheduling" approach; energy consumption obtained by the proposed method drops 10.7%.
Accurate estimation of volumetric errors is an important issue in machining operations. For this purpose, a kinematic error model is used to characterize machine tool’s related errors on its workspace. In this research, it is shown that when measuring the linear and positioning errors using a laser interferometer, part of the angular errors are converted to linear and positioning errors and their magnitudes are overestimated. These values are calculated twice in the models which use homogeneous transformation matrix since Abbe’s principle is not considered. In this article, a kinematic error model is proposed which eliminates this overestimation. This model’s methodology is based on rigid body kinematic and errors measurement by laser interferometer and can be generalized for all three-axis machine tools. A software package is developed to integrate the kinematic errors with the NC-codes. A workpiece is machined in the virtual environment and compared with a workpiece machined in real environment. It is shown that the kinematic error model developed in this research predicts the kinematic errors more accurately.
In this article, an integrated production–distribution model is presented for a manufacturer and retailer supply chain under inflationary conditions, permissible delay in payments, deterioration, imperfect production process and inspection errors. We assume that the first-stage inspection of the manufacturer is not perfect and makes inspection errors of Type 1 and Type 2. The second-stage inspection of the manufacturer is at the end of production period without inspection errors. Also, the demand is linear function of time. Once the retailer receives the lot, a 100% screening process of the lot is conducted without inspection errors, and the screening process and demand proceed simultaneously. The main objective is to determine the optimal inspection time and the optimal number of cycle such that the present value of the total cost is minimized. Finally, a numerical example and sensitivity analyses are provided to illustrate the proposed model using a proper algorithm.
Designing a cellular manufacturing system involves four major decisions: cell formation, cellular layout, operator assignment and cellular scheduling which should be considered, simultaneously. This article presents a new mathematical model to solve the cell formation, operator assignment and inter-cell layout problems, concurrently. The objectives of proposed model are minimization of inter–intra cell part movements, machine relocation cost and operator-related issues including hiring, firing, training and salary costs. Two numerical examples in both small and large sizes are optimally solved by the Lingo software to verify and validate the proposed mathematical model. Also, a sensitivity analysis is performed to analyze the behavior of operators in different production periods.
Nuclear steam turbines are well-known working in saturated wet-steam environment. The use of anti-corrosion material depositing or coating on the critical components and then machining to the required thickness with specific surface quality can be an effective and economical way to prevent critical components of steam turbines from corrosion and erosion. Inconel 182 can be this anti-corrosion material; however, a few literature has reported its machinability, not to mention its machinability at different overlay thickness. The objective of this study is to investigate the influence of the coated overlay thickness on microstructures and machinability of Inconel 182 overlays. First, the micro-hardness and microstructures of Inconel 182 overlays at different overlay thickness are studied. Afterwards, cutting forces, cutting temperature, surface roughness and the machined surface morphology at different overlay thickness are discussed. Finally, the prediction model for machining Inconel 182 overlays at different overlay thickness is established. The results indicate that the microstructures of Inconel 182 overlays strongly rely on overlays thickness and Inconel 182 electrode diameter (3.2 mm). The prediction model illustrates that the machinability of Inconel 182 overlays is acceptable at overlay thickness from about 0 to 2.1 mm; it is poor at overlay thickness from about 2.1 to 6.4 mm, and it is stable at overlay thickness from about 6.4 to 10 mm.
A double ball bar (DBB) is used extensively to evaluate the geometric and dynamic performance of three-axis machine tools by means of the XY, YZ and XZ planar circular tests. However, research using a DBB to test the rotary axes of five-axis machine tools simply, quickly and effectively is scarce. In this paper, a method having two sttif to identify the imprecision of the rotary axes caused by the position-independent geometric errors (PIGEs) is presented for a tilting rotary type five-axis machine tool using a DBB. The first step is designed to evaluate two rotary axes with one setup. Its advantage of fast diagnosis effectively reduces the machine down time, and thus can be employed as a quick testing approach of the machine tool. However, if some of the diagnosed errors fall outside their tolerances, a more accurate but slower check needs to be carried out due to the limitation of the first step. The second step aims to test the two rotary axes separately, each in two sub-sttif. By means of varying the position of the pivot, the A- and C-axes can be tested individually. Both sttif are performed with only one axis moving, thus simplifying the error analysis. Implementation of the proposed methods was carried out on a Hermle C600U five-axis machine tool. To show the validity of the method, the identified PIGEs are compensated for in each step, which suggests that the first step can be used as a fast and preliminary indication of a five-axis machine tool’s performance, whilst the second can be carried out if a more thorough evaluation is needed.
Interlayer burr formation in drilling of stacked aerospace materials is a common problem in aircraft assembly operations. Burrs formed at the interface of the stacked sheets need to be removed, and the deburring is a nonvalue but time and costs waste operation, particularly in automatic drilling and riveting assembly. This article presents an analytical model of the interlayer gap formation to predict the interlayer burr height, and drilling experiments were developed to understand the difference between the interlayer burr height and the interlayer gap. The impact of cutting force, spindle rational speed and feed rate was taken into consideration. Specific conclusions regarding the influence of the interlayer gap on burr formation were presented.
In modern manufacturing sectors, mechanical drilling of high-strength carbon fiber–reinforced polymer represents the most challenging task as compared to conventional low-strength carbon fiber–reinforced polymer drilling due to the extremely superior mechanical/physical properties involved. The poor machinability of the composite usually results in serious geometric imperfection and physical damage in drilling and hence leads to a large amount of part rejections. In this article, an experimental investigation concerning the cutting-induced damage when drilling high-strength carbon fiber–reinforced polymer laminates was presented. The studied composite specimen was a newly developed high-strength T800S/250F carbon fiber–reinforced polymer composite. A special concentration was made to inspect and characterize the phenomena of various cutting-induced damage promoted in the material drilling. The work focused on the study of the influence of cutting parameters on the distribution and extent of hole damage formation. The experimental results highlighted the most influential factor of feed rate and tool wear in affecting the final extent of induced hole damage when drilling high-strength T800S/250F carbon fiber–reinforced polymer. For minimizing the various damage formation, optimal cutting parameters (high spindle speed and low feed rate) and rigorous control of tool wear should be seriously taken when drilling this material.
In this study, femtosecond laser was used to create micro-structures on the flank face of a cutting tool. For the first time, a nature-inspired design (shape) of structure was created and explored. The inspiration for the nature-inspired design was the ball python (snake). This is because these creatures have high resistance to damage, originating from skin surface design feature. This was the main reason in replicating its scale design on cutting tool surface. Orthogonal cutting test was performed on AISI/SAE 4140 at the cutting speeds of 283 and 628 m/min and a feed of 0.1 mm/rev to study the effects of structure shapes. Results showed that nature-inspired design structures significantly reduced forces, temperature, compression ratio, contact length and power consumption. Characterisation of sticking and sliding contact was also made.
The ball end milling process is commonly used for generating complex three-dimensional sculptured surfaces with definite curvature. In such cases, variation of surface properties along with the machined surface is not well understood. Therefore, this article investigates the effect of machining parameters on the quality of surface in ball end milling of thin-shaped cantilever of Inconel 718. A distinct variation is also observed in the measured values of deflection of workpiece: surface roughness and surface damage in different regions, that is, fixed end, mid portion and free end of machined surface. The experiments were conducted according to the central composite design with four factors, namely, cutting speed, feed, workpiece thickness and workpiece inclination with tool path orientation. It is observed that the process parameters have statistically significant effect on machined surface of Inconel 718. Horizontal tool path condition during milling is most favourable in all aspects of surface quality with high speed and lower feed. The surface roughness values at the fixed end of plate are less as compared with that of mid portion and free end sides. Scanning electron microscope images show various defects such as side flow, smeared layer, microparticle, grooves and feed marks.
Surface quality and accuracy are the main factors which affect the performance and life cycle of the products. Due to the complexity of the machining process, it is difficult to evaluate the machined surface real time. Simulation of the machining process became the main method to predict and control the quality of the machined surface. This article developed a multi-scale simulation system to predict the overall geometrical features of the milled surface. The effects of locating errors, geometrical errors of the machine tool and tool deflections on the quality of the machined surface are included in the proposed model. Also, different strategies are employed to evaluate the macro-scale and micro-scale geometrical deviations of the machined surface to balance the time cost and accuracy. In comparison with the traditional method, both the form deviations and roughness feature of the machined surface can be predicted. Since the static and dynamic properties of the machining system were considered, both the stable and unstable cutting conditions can be analyzed by using the proposed method. At the end of this article, case studies are carried out to validate the proposed method. The effects of the locating errors, geometrical errors of the machine tool and cutting parameters on the quality of the machined surface are analyzed. The significance of their influences on the quality of the machined surface was investigated.
Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.
Computer-aided process planning is an important component for linking design and manufacturing in computer-aided design/computer-aided process planning/computer-aided manufacturing integrated manufacturing systems. Operation sequencing in computer-aided process planning is one of the most essential tasks. To solve the problem and acquire optimal process plans, operation sequencing is modeled as a combinatorial optimization problem with various constraints, and a novel modified ant colony optimization algorithm is developed to solve it. To ensure the feasibility of process plans, constrained relationships considered among operations are classified into two categories called precedence constraint relationships and clustering constraint relationships. Operation precedence graph based on constrained relationships is formed to get visual representation. To ensure good manufacturing economy, in the mathematical model for optimization, total weighted production cost or weighted resource transformation time related to machine changes, setup changes, tool changes, machines and tools is utilized as the evaluation criterion. To avoid local optimum and enhance global search ability, adaptive updating method and local search mechanism are embedded into the optimization algorithm. Case studies of three parts are carried out to demonstrate the feasibility and robustness of the modified ant colony optimization algorithm, and some comparisons between the modified ant colony optimization algorithm and previous genetic algorithm, simulated annealing algorithm, tabu search and particle swarm optimization algorithm are discussed. The results show that the modified ant colony optimization algorithm performs well in the operation sequencing problem.
A new approach is presented in this article for modeling and analysis of precise end-face grinding burr formation. The aim of this approach is to develop an automatic online deburring method that utilizes a precision motion control mechanism and effective deburring tools. Servo valve cores widely used in aerospace industry were employed as the workpiece in this study. After precision external grinding process, as a rule, the way of end-face grinding is adopted to get qualified working edges; the precision of these edges are generally required to be micron level or higher. However, after end-face grinding, the outside circle of the working edges will have burrs whose heights range from a few to dozens of microns, and the manual offline burr removal method currently adopted is not only uneasy to control accuracy but also easy for the working edges of the workpiece to lose its integrity and lead to a high rejection rate. In this article, the burr modeling and analysis procedure were used to get the corresponding formation mechanism of burr, and the online precision burr removal equipment was designed reasonably. Therefore, the effective removal of arising micro-burr from end-face grinding and the accuracy of the working edges were very well guaranteed, so as to improve the production efficiency.
Hybrid machining processes growing popularity in the processing of difficult-to-cut materials due to their distinct merits over individual machining processes attributed by an amalgamation of two or more machining mechanisms simultaneously. This research study deals with the response surface methodology and artificial neural network with backpropagation algorithm–based mathematical modeling of electro-discharge diamond grinding of Inconel 718 superalloy. The matrix experiments were designed based on central composite design. The wheel speed, current, pulse-on-time, and duty factor were chosen as control factors, while material removal rate and average surface roughness (Ra) were chosen as performance parameters. The analysis of variance test shows that the wheel speed is the major factor influencing both the material removal rate and the Ra and contributes 89.03% and 79.10% on material removal rate and Ra, respectively, followed by current which contributes 4.43% and 8.38% on material removal rate and Ra, respectively. The modeling and predictive abilities of developed artificial neural network model (4-24-2) were related to the response surface methodology model using root mean square error and absolute standard deviation. The predicted values of material removal rate and Ra by response surface methodology and artificial neural network are in close agreement with the actual experimental results.
To improve the machining accuracy and production efficiency of face gears, this article presents a generating milling method for the spur face gear using a five-axis computer numerical control milling machine and proposes a milling principle of the spur face gear using a milling cutter. Based on the milling principle and theory of gearing, a mathematical model of the spur face gear milling cutter is established, and the design parameters of the cutter are determined. Considering the requirements of machine motion during the face gear milling process, a five-axis computer numerical control milling machine is developed to produce the face gear. Based on the structure of the milling machine, a mathematical model of the spur face gear is established, and a milling method is proposed. The spur face gear milling cutter is manufactured, and the face gear milling experiments are conducted on the self-developed milling machine. The measurement results of the tooth surface deviations indicate that the maximum deviation is 22.6 µm, and that the machined spur face gear accuracy can meet the requirements of roughing. The experimental results verify the validity of the proposed generating milling method and demonstrate that the generating milling method is an effective approach to improve the accuracy and efficiency of the spur face gear.
Cutting tool path has significant effects on the performance of micro nozzles manufactured by micro machining. Different tool paths induced different directions of surface roughness. As for it, the manufacturers need to obtain optimal cutting tool path and cutting parameters. In this article, optimum machining parameters for the fabrication of micro Laval nozzle with two different end milling tool paths are presented. First, surface roughness models for different types of cutting tool paths are proposed. A case of machined nozzle surface is then given to verify the applicability of the developed roughness model. Second, theoretical profile geometries for the Laval nozzle to be manufactured are designed. Third, the influences of surface roughness on the nozzle performance parameters including total pressure, average outlet velocity and thrust are investigated through computational fluid dynamic analysis. Simulated performance parameters are contrasted with their theoretical values. It is found that for different tool paths, the nozzle of axial tool path has larger total pressure and average outlet velocity than that of circular tool path. Moreover, with surface roughness increasing, thrust decreases obviously when surface roughness Rz is larger than 4.8 μm. Micro end milling experiments based on axial tool path are then performed, and the optimum cutting parameters are obtained. Finally, a nozzle was manufactured with the axial tool path as well as the optimized cutting parameters.
Because of notable distortion in high-speed milling of grid sheet, it is difficult to choose a feasible processing scheme for this kind of workpiece. This article attempts to present a method to analyze the stress and deformation of grid sheet under different processing schemes based on a coupled mechanical–thermal finite element model, which provides a convenient and flexible platform to evaluate the performance of processing scheme in high-speed milling and optimize the cutting conditions. After a thorough analysis of the whole milling process of grid sheet, the tool path was discretized to make it convenient for the modeling of material removal process. An analytical thermal load calculation method and an experimental mechanical load calculation method were adopted to determine the loads exerted on the grid sheet. The constraint of the fixture was also considered, and finally, an ANSYS Parametric Design Language–based finite element method model was established. Based on this model, stresses and deformations under a given processing scheme with or without considering heat effect were compared, and it shows that cutting heat has great effect on the magnitude and distribution of deformation and stress. In addition, effects of some parameters on machining quality were investigated, and it was found that radial depth of cut has more impact than other parameters.
Energy conservation is one of the most important aspects of electrical discharge machining process in which the material removal is by means of spark erosion. Metal removal in wire electrical discharge turning is a complex erosion mechanism which involves melting, vaporization and rapid cooling of molten material. In this work, the significance of discharge energy on the performance of wire electrical discharge turning process, namely, material removal rate, surface finish, thickness of recast layer and surface crack, is analyzed. New model to estimate material removal rate and surface finish in wire electrical discharge turning process have been proposed. Erosion energy and kinetic energy imparted by electrons and average physio-thermal properties of work material are utilized for the modeling. Proposed models are validated by conducting experiments on AISI 4340 steel material. The results obtained from the model are well in agreement with the experimental values. The influence of discharge energy on surface crack and recast layer thickness is analyzed using scanning electron microscope micrographs and energy-dispersive x-ray spectroscopy analysis. Surface crack is observed at higher discharge energy. The thickness of recast layer increases with the increase in discharge energy. Three-dimensional surface topography reveals the turbulent nature of machining process resulted from transient erosion phenomena of wire electrical discharge turning process. Higher material removal rates of the order of about 0.06 g/min with consistent average roughness in the range of 4.5–5.5 µm at the expense of 1.6–2.6 J of discharge energy are achieved in this work. The proposed models can be utilized for machining of difficult to machine material by effective utilization of energy that leads to energy conservation in wire electrical discharge turning process.
In five-axis machining, stability of the machining process is determined not only by the combination of depth of cut and spindle speed but also the cutter postures (orientations). In this article, we propose to construct posture stability graphs to guide the selection of cutter postures during tool-path generation. Posture stability graph provides a partitioning of the allowable range of cutter postures, dividing it into stable and chatter zones. Using postures only from the stable zone, we can achieve chatter avoidance without the trouble of tuning other process parameters like spindle speed. Posture stability graphs are constructed by identifying the cutter orientations that would render the machining system borderline stable under the given machining conditions. These postures would make the boundaries between stable and unstable zones on the posture stability graph. Such a process is achieved by modelling the machining system as a 2-degrees-of-freedom spring-mass-damper system and applying the full-discretization method for chatter identification. Many experiments have been carried out, based on which the effectiveness of the posture stability graph approach has been verified.
A failure-prone manufacturing system that consists of one machine producing one type of product is studied. The random phenomena examined are machine breakdowns and repairs. We assume that the machine undergoes a progressive deterioration while in operation and that the machine failure rate is a function of its age. The aging of the machine (the dynamics of the machine age) is assumed to be an increasing function of its production rate. Corrective maintenance activities are imperfect and restore the age of the machine to as-bad-as-old conditions. When a failure occurs, the machine can be repaired, and during production, the machine can be replaced, depending on its age. When the replacement action is selected, the machine is replaced by a new and identical one. The decision variables are the production rate and the replacement policy. The objective of this article is to address the simultaneous production and replacement policy optimization problem in the context of manufacturing with deterioration and imperfect repairs satisfying the customer demand and minimizing the total cost, which includes costs associated with inventory, backlog, production, repair and replacement, over an infinite planning horizon. We thoroughly explore the impact of the machine aging on the production and replacement policies. Particular attention is paid to the verification of underlying mathematical results that guarantee the existence of optimal solutions and the convergence of numerical methods. Due to imperfect repairs, the dynamics of the system is affected by the system history, and semi-Markov processes have to be used for modeling. Optimality conditions in the form of the Hamilton–Jacobi–Bellman equations are developed, and numerical methods are used to obtain the optimal control policies (production (rate) and replacement policies). A numerical example is given to illustrate the proposed approach, and an extensive sensitivity analysis is presented to confirm the structure of the obtained control policies.
The perennial challenge for the industry is to make parts, assemblies and machinery lighter and more efficient. This has led to progressively wider application of composites due to their excellent strength, stiffness and corrosion resistance properties. Composite components are assembled predominantly by fastening, which makes drilling a common machining process for such components. Delamination of the component surface at entry and exit of the drill is a drilling defect frequently encountered. Assessment of the severity of the delamination is necessary for correction and improvement of the performance of the parts and assemblies. Over a period of time, several factors have been suggested as the index of delamination for comparison and control. Also, various techniques are being adopted to measure the extent and severity of delamination so as to calculate the assessment factor. This study aims to present and review the different means and methods for the assessment of delamination.
In this study, tool wear and chip formation during the drilling process of AISI 1045 material using plasma-nitrided high-speed steel drill bits were experimentally investigated. Two uncoated and plasma-nitrided drill types were used in the experiments. First, commercial drill bits were subjected to the plasma nitriding process. Following this, the drilling processes were carried out at various feed rates and cutting speeds. A sensitive computer numerical control machine was used in the experiments. Tool wear was determined using scanning electron microscopy and chips obtained from the drilling process were observed under microscopy. Finally, the relationship between the chip cross section and tool wear was determined using statistical analysis. It was concluded that the mechanical properties of uncoated high-speed steel drill bits improve significantly through the plasma nitriding process. Less tool wear and a good chip formation were observed with the improvement of the mechanical properties. It was determined that there is a relationship between the chip section and wear.
This article provides the design and fabrication details of a new technique to build a microfluidic device with two parallel substrates and a silicone gasket. The fabrication process uses screen printing technology offering fast and low-cost microdevices without the need for high-cost fabrication equipment and special photoresist processes. Hermetic microfluidic channels of 300 µm width and 50 µm height having parallel facing electrodes on two substrates are made with simple serigraphy technique using silicone rubber. The fabricated devices were experimentally tested for detection and characterization of polystyrene particles and living cells by negative and positive dielectrophoresis. The reported technique enables simple manipulation, centering, detection and characterization of living cells at low and high frequencies.
Hot stamping process has been regarded as one of the most attractive processes to produce high-strength parts with merits of low-forming load and small springback. However, the elongation of the hot-stamped parts is small, so the ability of crash resistance is limited. Recently, a novel hot stamping process integrated with quenching and partitioning treatment has been presented to improve the elongation of the final parts. In this article, the quenching and partitioning hot stamping process is further studied using the boron steel B1500HS, and the feasibility is verified by a series of quenching and partitioning tests followed by mechanical tests and microstructure observations. Moreover, an experimental tool for quenching and partitioning hot stamping process is first proposed in this article, where both air cooling device and heating system are designed, and a U-channel part is produced. Finally, in order to illustrate the active role of high elongation that the quenching and partitioning hot stamping process archived, numerical simulation of crash test for a B-pillar sample is conducted using finite element analysis software LS-DYNA.
Blasting erosion arc machining is a novel electrical erosion process depending on the hydrodynamic arc-breaking mechanism to achieve a reliable high-efficiency machining. In blasting erosion arc machining, the high-velocity fluid field in the discharging gap is the precondition of the mechanism to control arc plasma to efficiently remove workpiece material. Therefore, this study mainly investigates the influence of flushing holes on the fluid field distribution directly and on the machining performance indirectly. Three multi-hole solid electrodes with different types of flushing holes are designed out according to the distributing principle. The influence of their flushing holes on the fluid field is conducted by a comparison fluid simulation which demonstrates that the electrode with flushing-hole diameters decreasing gradually from the inner to the outer in the radial direction attains the best flushing velocity distribution on the workpiece surface. Furthermore, the influence of their flushing holes on the blasting erosion arc machining performance is investigated by a comparison machining experiment in order to verify the comparison results of fluid field simulation. The experimental results illustrate that these electrodes have very different machining performance when machining nickel-based high-temperature alloy GH4169 (similar to Inconel 718) under the conditions of same discharge peak current and flushing inlet pressure. The electrode with the best flushing velocity distribution rather than with the highest velocity at a particular point achieves the best machining performance of the highest material removal rate, the least relative tool wear ratio and the least surface roughness (Ra), indicating an optimized design of flushing holes in the multi-hole solid electrode.
Fused deposition modelling is an efficient rapid prototyping process used to rapidly fabricate three-dimensional solid objects with complicated geometries. Many process parameters affect the fused deposition modelling process and their settings influence the quality of the specimen. This article investigates the effect of raster angle on surface roughness (along and across the length direction) and mechanical properties (tensile and flexural strength) of fused deposition modelling parts built at 10 different raster angles (0°–90° at 10° interval). All parts are built using acrylonitrile butadiene styrene P430 material. Surface roughness for circular and parabolic curved surfaces is also measured when specimens are built at different raster angles. Fracture surfaces are inspected with scanning electron microscope to study the modes of failure under different loading conditions. The samples where raster angle is 0° and layers are deposited along the length of the specimen exhibited optimal mechanical strength and good surface finish (when measured along the length). Scanning electron microscope results reveal that for 0° raster angle, failures are mainly due to pulling and rupture of fibres and for 30° and 60° raster angle, failure is due to brittle shear in a direction parallel to raster orientation. Due to the presence of number of heating and cooling cycle in 90° raster orientation, interlayer cracking and distortion of raster take place leading to lower strength.
One of the primary processes for the production of composite parts is the liquid composite molding process. This process is based on the injection of resin into a mold, which is usually metallic. Today, studies are being undertaken to produce these molds using Hextool™, a carbon fiber–reinforced thermosetting plastic. The molds, constructed by draping prepregs, must be finished by free-form machining to ensure the dimensional and surface quality requirements. An arithmetic roughness of 0.8 µm is required, and this quality is not attained by milling operations. Thus, a manual polishing operation is necessary. However, to minimize the time taken by this manual operation, it is necessary to verify the roughness obtained by milling. Thus, the work presented in this article consists first of a study of the capability of milling to produce molds from Hextool with given surface quality requirements. The conclusion of this study is to define values of radial depth of cut to attain a surface quality with minimum machining time. Second, this work highlights how to replace the manual polishing operation by a machining operation with an abrasive diamond tool. Thus, the capability of an abrasive diamond tool to machine a mold with high surface requirements is discussed.
High-efficiency deep grinding experiments of Inconel 718 nickel-based superalloy was carried out with the porous metal-bonded cubic boron nitride superabrasive wheel, in which the uniform and large pores were formed by the broken alumina bubble particles in the working layer after wheel dressing. Grinding temperature, energy partitioning into workpiece, and wheel wear were investigated. Results obtained show that long maintenance of low grinding temperature, that is, 50 °C–170 °C, is obtained in high-efficiency deep grinding with the porous metal-bonded cubic boron nitride wheel. The energy partitioning into the ground workpiece is ranged from 2% to 6%, which is smaller than that with the conventional vitrified cubic boron nitride wheels and alumina abrasive wheels. Sufficient storage space for chips and coolants contributes to the excellent performance of the porous metal-bonded cubic boron nitride wheel in high-efficiency deep grinding. Abrasion wear and grain fracture are the dominant wear patterns of the porous cubic boron nitride wheel in the steady wear stage, while chips loading and grain pullout play a critical role in the final dramatic wear behavior of the porous wheel.
Tungsten inert gas welding is extensively used in aerospace applications due to its unique ability to produce higher quality welds compared to other conventional arc welding processes. However, most tungsten inert gas welding is performed manually, and it has not achieved the required level of automation. This is mostly attributed to the lack of process knowledge and adaptability to complexities, such as mismatches due to part fit-up and thermal deformations associated with the tungsten inert gas welding process. This article presents a novel study on quantifying manual tungsten inert gas welding, which will ultimately help intelligent automation of tungsten inert gas welding. Through tungsten inert gas welding experimentation, the study identifies the key process variables, critical tasks and strategies adapted by manual welders. Controllability of welding process parameters and human actions in challenging welding situations were studied both qualitatively and quantitatively. Results show that welders with better process awareness can successfully adapt to variations in the geometry and the tungsten inert gas welding process variables. Critical decisions taken to achieve such adaptations are mostly based on visual observation of the weld pool. Results also reveal that skilled welders prioritise a small number of process parameters to simplify the dynamic nature of tungsten inert gas welding process so that part variation can be accommodated.
Traditional parallel mechanisms are usually characterized by small tilting capability. To overcome this problem, a 3-degree-of-freedom parallel swivel head with large tilting capacity is proposed in this article. The proposed parallel swivel head, which is structurally developed from a conventional 3-PRS parallel mechanism, can achieve a large tilting capability by means of structural improvements. First, a modified spherical joint with a maximum tilting angle of ±120° is devised to diminish the physical restrictions on the orientation workspace. Second, a UPS typed leg is introduced for the sake of singularity elimination. The superiority of the proposed parallel swivel head is theoretically proved by investigations of singularity-free orientation workspace and then is experimentally validated using a prototype fabricated. The theoretical and experimental results illustrate that the proposed parallel swivel head has a large tilting capacity and thus can be used as swivel head for a hybrid machine tool which is designed to be capable of realizing both horizontal and vertical machining.
The gating system design for a die-casting die is a non-trivial task that involves a number of steps and computations, in which many factors related to part design, material, and process need to be accounted. In case of a multi-cavity die-casting die, the non-triviality of the gating system design increases manifold. The main contribution of this article is to develop a computer-aided system for design of gating system for multi-cavity die-casting dies. The proposed system applies design knowledge and rules, accounting for various influencing factors to design gating system elements and generate their computer-aided design models in an efficient manner. To demonstrate the capabilities of the developed system, the results for an industrial case study part are presented. We expect that the proposed system would help reduce manufacturing cost and lead time, alongside bridging gaps between design and manufacturing of the die-casting process.
Traditionally, metal cutting fluid or lubricant is used in finishing operations of high-speed machining process to reduce the rate of tool wear, which in turn will improve surface quality. In automobile and aerospace industries, minimum quantity lubrication technique is considered to provide the same level of performance as the flood coolant method and offers financial benefits by saving coolant direct and associated costs. However, scant research work has been done on minimum quantity lubrication applications in the die and mould manufacturing industry. In this study, the effects of dry, flood and minimum quantity lubrication machining on surface roughness, tool wear, dimensional accuracy and machining time of hardened steel mould inserts were compared. The results revealed that there were no significant differences between these three lubrication methods. More in-depth experimental study of dry and minimum quantity lubrication machining was then carried out using the design of experiments technique. In terms of surface roughness and tool wear, there were again no significant differences. Nevertheless, minimum quantity lubrication machining produced more accurate results than dry machining in dimensional deviation. The regression models show that feed-rate (fz) has a larger effect on surface roughness and machining time than step-over (ae), while depth of cut (ap) has no significant effect on surface roughness. Based on the test piece shape, a shortest possible machining time of 3.55 h and a good surface finish of 0.28 µm can be achieved using a small feed-rate (0.03 mm/tooth), a large step-over (0.1 mm) and a large depth of cut (0.2 mm). This work shows that when combining the minimum quantity lubrication technique with the right cutting conditions in modern die and mould manufacturing, machining time and polishing time can be saved, which leads to an overall saving in production cost. Using the dry and minimum quantity lubrication techniques for different finish machining situations can therefore be a good economical solution.
In gas metal arc welding, like other welding techniques, the quality of welded joint may be described in terms of weld bead geometry and the presence of welding defects. In turn, the characteristics of welding signals, such as voltage, current and sound, may be used to predict and improve the quality of welded joint. In this work, two sets of adaptive neuro-fuzzy inference system have been used to predict and improve the weld quality characteristics. The required data for modeling were obtained from 57 experiments based on D-optimal design of experiments. The first set is developed to predict the possible welding defects (discontinuity, lack of fusion and overlap) and shape factor of the weld bead. These "predicting adaptive neuro-fuzzy inference system models" have been developed using 13 statistical parameters of the sound, voltage and current signals. The objective of the second set of models, called "improving adaptive neuro-fuzzy inference system models," is to adjust the input welding parameters in such a way that the weld defects are minimized. These models simulate the experiences of professional human welders as the learning databases. Verification tests reveal that the proposed predicting adaptive neuro-fuzzy inference system models can accurately estimate the main weld quality indices in actual gas metal arc welding process. Moreover, experimental results for improving the adaptive neuro-fuzzy inference system models confirm that the defects of faulty weldment can be eliminated after applying the process parameters settings given by these models. The proposed adaptive neuro-fuzzy inference system models may pave the way in assisting the human welder to predict and enhance the weld quality characteristics.
During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.
The dynamic coupling problem for the self-designed "3 parallel 2 series" mixed-type numerical control machine tool is studied based on the singular constraints and position coupling factors in order to ensure that the machine can have better dynamic characteristics and a higher quality of parts during the process of machining complex surface. This article puts forward a method based on singular constraints and the coupling factor. A whole dynamic coupling model of series and parallel mechanism is established and the coupling factors are determined. Numerical and parameter simulations of mechanism are analyzed and the real working space is obtained. And this article takes the simulation of the process of machining complex part and the force of the machine tool. The simulation results show that the established dynamics model is credible and reliable on the basis of considering singular constraints and position coupling factors. It is proved that the simulation data can correspond to the established model and the situation of force and kinematic suits the working mechanism. The cutting experiment of complex surface parts was took and the machine tool was run more smoothly and faster than the conventional machine tools. The velocity of the machine is regular and circular and there are no kinematic singularity data on the machine’s trajectory. The trajectory of the tool is in the working space completely and the accuracy of the part is good. The surface roughness results show that the kinematics accuracy of the machine tool is good. The interference fringe results show that the force of the machine tool is uniform. As there is no singular coupled vibration and collision, it is proved that the theoretical analysis is correct. The dynamics model of 3PTT serial and parallel mechanism is complete in this article. And the working space of the mechanism is obtained on the base of analysis of the singular constraints and position coupling factors. The article has carried out the dynamic simulation and processing experimental verification. Not only the method and process of this article was solved by dynamics coupling problem of 3PTT-2R numerical control machine tool actively, real-time and effectively, but also it was laid a foundation for accurate control of numerical control machine tools.
A reliable system means being able to perform its intended functions. Therefore, ensuring performing of its required functions will help to enhance its reliability. For a manufacturing system (e.g. computer numerical control machines), there are a large number of functions, which complicate and make analysis difficult. In this article, a logical and systems approach of graph theory, which is effective to eliminate such difficulties, is employed. The graph theoretic models do consider the system structure explicitly and are applied to model functions at various hierarchical levels of a manufacturing system. These function digraph models are analysed using matrix approach to examine the cause and effect, which helps to evaluate importance of the function and hence provide direction for system reliability enhancement. A step-by-step methodology is presented, which is illustrated by an example of manufacturing system: computer numerical control drilling machine.
In computer-aided design for moldings, automatic generation of parting curves is a crucial design task that has an influence on the entire mold structure. This article proposes a hybrid approach for determining the parting curves of free-form computer-aided design models. Based on the analysis of the geometric properties of specific entities and mathematical conditions, different sets of moldable surfaces for two-half molds and side cores are identified. All surfaces that do not contribute to the parting curves can be subtracted from these surface sets. The proposed parting curve is generated based on the combination of both the outermost boundary edges and the visible silhouette segments of the relevant surfaces. By the techniques of silhouette detecting, edge projecting, and ray testing, the proposed algorithm overcomes the problems found in conventional research that cannot guarantee that the outermost curves generated are the actual silhouette of a free-form surface. In addition, by eliminating all irrelevant surfaces and without using the surface approximation method, the proposed approach achieves the goals of obtaining high accuracy coupled with high performance. Two examples of industrial models are used to demonstrate the performance and robustness of the proposed algorithm. The approach is generic in nature, which allows it to be applied to any complex geometry in three-dimensional mold design.
Manufacturing environment is always changing due to unexpected reasons, including urgent job insertion, unavailability of machine tools, and changes of production planning, which has imposed significant challenges for numerical control programming, as numerical control programs are always not available any more for changed manufacturing resources. Traditional numerical control programming mode cannot adapt to the new manufacturing environment, and this problem becomes especially pressing for large manufacturing enterprises with production characteristics of small batches and large varieties. In order to address this issue, a feature-based adaptive numerical control programming method for changing manufacturing environment is proposed. A framework including preprocess module and postprocess module is constructed, and the flexibility of the numerical control program is realized through the function separation of the two modules. A feature-based information model including geometric and process information is established for flexible numerical control program generation when manufacturing resources are changed. About 75% numerical control programming work which is manufacturing resource free is done by preprocess module, and the rest is done by postprocess module for changing manufacturing environment. The implementation of the prototype system for the numerical control programming of a typical aircraft structural part shows the feasibility of the proposed method.
This study seeks to develop an efficient way of quantitatively investigating the intrinsic size effect in machining. This is accomplished by carrying out the following procedures: conducting the pure two-dimensional orthogonal machining with the cutting edge radius and the uncut chip thickness varied, investigating the relation between the cutting edge radius and the specific cutting energy when the uncut chip thickness is fixed, and then estimating the specific cutting energy for a perfectly sharp tool by extrapolating the relations obtained for different values of the uncut chip thickness. Finally, the usefulness of the developed method is validated by showing that the estimate of the specific cutting energy for a perfectly sharp tool can be effectively utilized for understanding and modeling the intrinsic size effect, especially the material length scale, in machining.
The key to improve the machining quality of workpiece is to decrease the process fluctuation, which requires identifying the fluctuation sources first. For small-batch multistage machining processes of complex aircraft parts, how to identify the fluctuation sources efficiently has become a difficult issue due to the limited shop-floor data and the complicated interactive effects among different stages. Aiming at this issue, a fluctuation evaluation and identification model for small-batch multistage machining process is proposed based on the sensitivity analysis theory. In order to improve the data utilization, an analytical structure of the fluctuation evaluation and identification model for small-batch multistage machining process is presented, which comprises four levels, namely, part level, multistage level, single-stage level and quality feature level. Corresponding to the four levels in the analytical structure, four fluctuation analysis indices are proposed to quantitatively evaluate the fluctuation level of different parts and identify the weak stages and elements that result in the abnormal fluctuation in the process flow. A five-stage deep-hole machining process of aircraft landing gear is used as a case to verify the proposed model.
Laser-assisted mechanical micromachining offers the ability to machine difficult-to-cut materials, like superalloys and ceramics, more efficiently and economically by laser-induced localized thermal softening prior to cutting. Laser-assisted mechanical micromachining is a micromachining process with localized laser heating which could affect the cutting forces and the machined surface integrity. The residual stresses obtained in the laser-assisted mechanical micromachining process depend on both mechanical loading and the laser heating. This article focuses on the experimental process characterization and prediction of the cutting forces and the residual stresses in a laser-assisted mechanical micromachining–based orthogonal machining of Inconel 625. The results show that the laser assistance reduces the mean cutting forces by ~25% and enhances the normal compressive residual stress at the surface by ~50%. Since microscale residual stress measurement is very time-intensive, a coupled-field thermo-mechanical finite element model of laser-assisted mechanical micromachining has been developed to predict the temperature, cutting forces and the residual stresses. The cutting forces and residual stresses’ predictions are in good agreement with the measured values during machining. In addition, parametric simulations have been carried out for laser power, cutting speed, cutting edge radius, rake angle, laser location and laser beam diameter to study their effect on cutting forces and surface residual stresses.
Powder metallurgy plain carbon steel (Fe–0.5% C) replaces gradually the conventional C45 steel in all industrial sectors due to its comparable strength and better metallurgical properties. This research investigates the influence of density/porosity of powder metallurgy plain carbon steel on wear characteristics and optimizes the wear working parameters to establish minimum wear loss and coefficient of friction during wear using Taguchi-grey relational optimization analysis. The sintered steel preforms were subjected to uni-axial compressive load (cold upset) to obtain various percentage theoretical densities. The wear test specimens made out of various densities of the sinter-forged plain carbon steel were used to conduct wear tests as per the test plan generated by the Design Expert software. The optical and scanning electron microscope images taken from the worn test specimens were used for the investigations of wear mechanisms of the alloy steel. It is observed from the wear test results that the porosity in the powder metallurgy plain carbon steel has a vital role in wear properties of the steel. It has also been found that the optimized working parameters such as speed and load are found as same irrespective of the densities of the plain carbon steel.
This article presents a crystal plasticity methodology to evaluate the AA1050 sheet formability. In order to determine the orientation distribution of the crystals, initial texture of the material is measured through X-ray diffraction technique. Also, the stress–strain behavior of the material is determined by performing tensile test. In order to simulate the path-dependent crystal plasticity behavior of body-centered cubic crystal structures, a UMAT subroutine that employs the rate-dependent crystal plasticity model along with the power law hardening was developed previously by the authors and linked to the finite element software ABAQUS. This subroutine was further developed to simulate face-centered cubic crystal structures. The second-order derivative of sheet thickness variations with respect to time is considered as the instability factor, and forming limit diagram of the material is predicted. In order to assess the validity of formability prediction results for face-centered cubic materials, forming limit diagram of AA1050 sheet is also experimentally extracted by conducting hemi-spherical punch test. It is observed that the predicted forming limit diagram is in agreement with the experimental results. Finally, the prediction accuracy in different regions of forming limit diagram is discussed and some suggestions for further improving the accuracy are made.
The accurate modeling of thermal gradients and distortion generated by directed energy deposition additive manufacturing requires a thorough understanding of the underlying physical processes. One area that has the potential to significantly affect the accuracy of thermomechanical simulations is the complex forced convection created by the inert gas jets that are used to deliver metal powder to the melt pool and to shield the laser optics and the molten material. These jets act on part surfaces with higher temperatures than those in similar processes such as welding and consequently have a greater impact on the prevailing heat transfer mechanisms. A methodology is presented here which uses hot-film sensors and constant voltage anemometry to measure the forced convection generated during additive manufacturing processes. This methodology is then demonstrated by characterizing the convection generated by a Precitec® YC50 deposition head under conditions commonly encountered in additive manufacturing. Surface roughness, nozzle configuration, and surface orientation are shown to have the greatest impact on the convection measurements, while the impact from the flow rate is negligible.
This article studies regenerative chatter in single-point face-machining at nominally constant speed under continuous conditions. A temporal model for rotational speed was developed and experimentally verified. The resulting rotational time-delay was cast into the classical force feedback mechanism for chatter. A chatter model was formulated to allow slight spindle speed variation about the temporal model. The modified method of steps was then employed to solve the tool vibration in time-domain allowing one (single-degree-of-freedom) or two (2-degree-of-freedom model) vibrational modes. Exploratory facing experiments using a grooving tool were conducted on a nickel alloy workpiece. It was found that the tool was more susceptible to chatter at larger diameters. It appeared that the single-degree-of-freedom model captured the most relevant of the observed phenomena while cutting without spindle speed variation, however, neither the 1-degree-of-freedom nor the 2-degree-of-freedom models could effectively capture the experimentally observed chatter evolution characteristics while cutting with spindle speed variation.
Forming of flat sheets into shell conical parts is a complex manufacturing process. Hydrodynamic deep drawing process assisted by radial pressure is a new hydroforming technology in which fluid pressure is applied to the peripheral edge of the sheet in addition to the sheet surface. This technique results in higher drawing ratio and dimensional accuracy, better surface quality, and ability of forming more complex geometries. In this research, a new theoretical model is developed to predict the critical rupture pressure in production of cone cups. In this analysis, Barlat–Lian yield criterion is utilized and tensile instability is considered based on the maximum load applied on the sheet. The proposed model is then validated by a series of experiments. The theoretical predictions are in good agreement with the experimental results. The effects of geometrical parameters and material properties on critical rupture pressure are also studied. The critical pressure is increased with increase in the height ratio, strain hardening exponent, and anisotropy. Higher punch nose radius expands the safe zone. It is shown that the critical pressure decreases for drawing ratios higher than 4.
In this article, a new manufacturing method is introduced to shape circular tubes into columns with triangular cross-section by the elastoforming process. Also, a theoretical analysis is performed to derive a theoretical formula for predicting total dissipated energy that is required for the forming process. For this purpose, V-shape dies with different angles are designed and some aluminum and brazen tubes with different characteristics are prepared. The circular tubes in the empty and filled conditions are compressed between a rigid V-shape die and a flat punch, and during the plastic deformation under the lateral loading, the tubes are shaped into the triangular sections. Considering different tube lengths, outer diameters and wall thicknesses, the specimens are categorized. Also, some of the samples are filled by cylindrical polyethylene Teflon with different thicknesses to investigate the effects of Teflon-filler on the shaping process of the triangular columns. The experiments show that using the cylindrical Teflon-filler, deformation mode of the triangular tubes improves, significantly. In addition, experimental observations of the deformation modes illustrate that there is an optimum value for wall thickness of cylindrical Teflon-filler and the tubes with the optimum Teflon-filler forms close to desirable triangular shape. The results show that by increasing tube wall thickness, probability of crack initiation and fracture reduces. Furthermore, comparison of estimations by the presented theory and the corresponding experimental measurements show an acceptable agreement, in both of empty and filled conditions.
Investment casting process is known to its capability of producing clear net shape, high-dimensional accuracy and intricate design. Consistent research effort has been made by various researchers with an objective to explore the world of investment casting. Literature review revealed the effect of processing parameters on output parameters of cast specimen. This article highlights the advancements made and proposed at each step of investment casting and its hybridization with other process. Besides, investment casting has always been known to manufacture parts such as weapons, jewellery item, idols and statues of god and goddess since 3000 BC; this article reviews the present applications and trends in combination of rapid prototyping technique as integrated investment casting to serve in medical science. Advancements in shell moulding with incorporation of fibre and polymer, development of alternative feedstock filament to fused deposition modelling are duly discussed. The aim of this review article is to present state of art review of investment casting since 3200 BC. This article is organized as follows: in section ‘Introduction’, introduction to investment casting steps is given along with researches undertaken at each step; in section ‘Rapid prototyping technique’, background is given on the concept of rapid prototyping technique by examining the various approaches taken in the literature for defining rapid prototyping technique; section ‘Biomedical applications of RPT’ presents the medicine or biomedical applications of investment casting and rapid prototyping technique; section ‘Future trends’ provides some perspectives on future research and section ‘Conclusion’ closes the article by offering conclusions.
Determining the movement errors due to mechanical parts in computer numerical control devices is an important part of studying manufacturing and production. The propelling mechanical system of a computer numerical control device consists of engine, coupling, bearing, knot and leading rail. Each of these parts has an error value which causes manufacturing error in producing industrial parts. Although using closed-loop system has helped to solve this problem, still there are systems that use open loop. In this study, using Mooney–Rivlin model for flexible couplings, we calculated the errors due to the deformation of elastomeric medium, which is made of thermoplastic polyurethane. Using the ANSYS software, we simulated the three-dimensional model of medium to obtain elastic deformation. The loading type was chosen in terms of torque and stepper revolution of engine. At fixed 500 r/min, the effect of torque and engine stepper on the deformation was investigated, and the results obtained were compared with the simulations from experimental work on a computer numerical control desk with stepper 1.8 and 2.4 N m and ABBA coupling of model SRG-40C and ball screw of milled diameter 25 pitch 5 class C which showed a good confirmation.
This research proposed an advance in the prediction of the in-process surface roughness during the ball-end milling process by utilizing the wavelet transform to monitor and decompose the dynamic cutting forces. The chatter detection system has been adopted from the previous research of the author to avoid the chatter first, and hence, the dynamic cutting force ratio is introduced to predict the in-process surface roughness during the normal cutting by taking the ratio of the decomposed dynamic cutting force in X axis to that in Z axis. The Daubechies wavelet transform is employed in this research to analyze the in-process surface roughness. The experimentally obtained results showed that the surface roughness frequency occurred at the same level of the decomposed dynamic cutting forces although the cutting conditions are changed. It is understood that the in-process surface roughness can be predicted effectively under various cutting conditions referring to the proposed monitoring system.
This study explores about enhancing the permeability of the ceramic shells used in the investment casting process using cheaply available sawdust particles. An increase in shell’s permeability augments the cooling rate of the casting which enhances its mechanical properties. It was found that the inclusion of sawdust particles into the ceramic slurries exhibited positive impact on the shell’s permeability. It is a well-known fact that electromagnetic stirring process increases the mechanical properties of the castings, but its effect on casting shrinkage has never been realized. Thus, this study further throws light on the impact of electromagnetic stirring in reducing the shrinkage and improving the tensile strength of the casting. In a nutshell, it was found that the final product quality of the investment cast part improved by the combinational treatments adopted in this research work.
Industrial environments can use several layout setups according to their convenience based on item diversity, ways of production and market demand. This work focuses on design of manufacturing cell formation. A well-known type of production layout in industrial engineering that allows meeting a diversity of production requirements and operational flexibility is the cellular manufacturing. Among the various techniques and approaches applied to manufacturing cell formation, this article uses the firefly metaheuristic algorithm as an optimization engine. Such modern stochastic optimization algorithm can tackle non-convex, non-smooth, non-continuous and non-differentiate objective cost functions making them gradient independent and suitable to manage such problems. The adopted methodology relies on comparing the obtained efficiency and efficacy (clustering) parameters in the cell formation layout with several well-established benchmark examples found in the literature. The results show that the use of efficacy parameter is desirable if the focus relies on clustering manufacturing cell formation, however, the use of efficiency parameter can also lead to useful and cost-effective layouts at the expense of cell clustering. Some of the results also indicate improvements in the efficacy parameter relative to the benchmarked examples with a slightly enhanced layout formation that proves and justifies the suitability for the firefly metaheuristic algorithm.
As a component of knowledgeable manufacturing systems, the structure of flow shop–like knowledgeable manufacturing cells is similar to that of a flow shop, thus representing an NP-hard issue. Here, we propose a self-evolutionary algorithm that exhibits learning ability and is composed of learning and scheduling modules. Unlike traditional scheduling algorithms, whose performances remain unchanged when the procedure is coded, the performance of the algorithm proposed in this study gradually improves as the learning process continues. The self-evolutionary ability is realized through the training of a hybrid kernel support vector machine. The hybrid kernel support vector machine was designed to approximate the value of the Q-function to select the appropriate action for the scheduling module and thus to obtain the optimal solution. An iterative process of value based on the Q-learning was adopted to train the hybrid kernel support vector machine to gradually enhance the algorithm’s efficiency and accuracy. The extracted state features of the flow shop–like knowledgeable manufacturing cells serve as inputs to hybrid kernel support vector machine for easy generalization of the learning results. The action exerted on a feasible solution is also defined as the input of the hybrid kernel support vector machine. The computational results show that the performance of the proposed procedure improves as the learning process progresses. Data from the computation and comparisons with other algorithms verify the validity and efficiency of the proposed algorithm.
Laser line heating is a plate bending technique. It is produced due to the heating effect of a laser beam when irradiated over a suitable heating path. In this work, the effect on angular deformation under different operating parameters, such as energy (in terms of laser power), scanning speed and number of passes along with the thickness of the substrate material, was studied under straight line scanning schemes. In this experiment, CO2 laser has been used and the substrate material used is the mild steel sheet. The effect of each operating parameter was taken into account to find the optimum process parameter. The design of experiment has been applied with the help of Taguchi method, and the results were obtained and analysed with the help of analysis of variance and Taguchi analysis (signal-to-noise ratio), for the determination of the optimized values of the operating parameters with their effect towards angular deformation in the process. A regression analysis also has also been performed to obtain a suitable co-relationship between bending angle and other operating parameters.
In order to achieve the precision bending deformation, the effects of process parameters on springback behaviors should be clarified preliminarily. Taking the 21-6-9 high-strength stainless steel tube of 15.88 mm x 0.84 mm (outer diameter x wall thickness) as the objective, the multi-parameter sensitivity analysis and three-dimensional finite element numerical simulation are conducted to address the effects of process parameters on the springback behaviors in 21-6-9 high-strength stainless steel tube numerical control bending. The results show that (1) springback increases with the increasing of the clearance between tube and mandrel Cm, the friction coefficient between tube and mandrel fm, the friction coefficient between tube and bending die fb, or with the decreasing of the mandrel extension length e, while the springback first increases and then remains unchanged with the increasing of the clearance between tube and bending die Cb. (2) The sensitivity of springback radius to process parameters is larger than that of springback angle. And the sensitivity of springback to process parameters from high to low are e, Cb, Cm, fb and fm. (3) The variation rules of the cross section deformation after springback with different Cm, Cb, fm, fb and e are similar to that before springback. But under same process parameters, the relative difference of the most measurement section is more than 20% and some even more than 70% before and after springback, and a platform deforming characteristics of the cross section deformation is shown after springback.
An ultra-precision ball rotating displacement measurement setup based on laser focus deviation was presented. The setup is capable of measuring ultra-precision ball rotating displacement at nanometer sensitivity. The experiment results indicated that the method has high repeatability and potentially with high throughput. A dual-probe setup is also studied to evaluate diameter variation in a ball with errors introduced by misalignment, while spindle radial vibration being automatically eliminated. Optical probe-based ultra-precision ball displacement and diameter variation measurement are suitable for in situ application with high throughput and repeatability.
In this study, a new electrostatic field–induced electrolyte jet electrical discharge machining method has been proposed, which can automatically generate the tool electrode. Then, a series of experiments have been carried out to reveal the machining mechanism and test the machining ability of this method. The continuous observation experiments and the online current detection experiments have demonstrated that the electrolyte jet discharge machining is a pulsing, dynamic and cyclic process. Moreover, the 20-min time long reverse polarity experiments on the silicon surface have revealed that the machining is an electrical discharge machining process during the negative polarity machining; however, in the positive polarity machining, it is a hybrid electrical discharge machining and electrochemical machining process. Furthermore, the craters as small as 2 µm in diameter on stainless steel and silicon are produced by this electrolyte jet electrical discharge machining, which has proved the micro-machining ability of this method.
Effect of aging treatment on mechanical properties of an age-hardenable aluminum alloy after equal channel angular pressing at room temperature has been investigated using hardness, stress–strain behavior and surface fractography. Aluminum alloy 7075 was pressed after solution treatment. Yield stress, ultimate stress and hardness of pressed samples have increased significantly compared with those of coarse grain, but the elongation to failure has decreased. Also the pressed specimens were subjected to aging treatment at room temperature and temperatures of 80 °C, 100 °C, 120 °C and 140 °C to obtain the optimized strength and ductility. The results indicated that post–equal channel angular pressing aging at 80 °C has resulted in the maximum strength, and natural aging has resulted in good ductility and acceptable strength. It confirmed the fact that there is a potential in obtaining high strength and good ductility in age-hardenable alloys employing severe plastic deformation and subsequent aging.
Electric discharge sawing process is a novel process for the enrichment of capabilities of electric discharge machining. The process has been developed to cut materials at greater depths where the effect of flushing becomes ineffective. During electric discharge machining at greater depths, ineffective flushing prevents debris and carbon particles from leaving the machining zone and gets accumulated in the sparking zone reducing the spark efficiency. This reduces material removal rate and causes arcing or short circuiting which may damage the workpiece and/or tool surface. In the present experimental endeavor, a new process capable of preventing debris accumulation during machining of slots at large depth and subsequently increasing material removal rate has been developed. In the process, a reciprocating motion is given to the tool blade similar to the power hacksaw blade. An experimental investigation based on central composite design has been conducted on hybrid metal matrix composite to evaluate the effect of input parameters on material removal rate and tool wear rate. It has been found that the electric discharge sawing process is quick and effective as compared to the conventional cutting process.
In this experimental research, the electrode caps are investigated for deterioration under the resistance spot welding technology. The research was fundamentally conducted using two different electrode actuation systems to understand the wear and tear factors of electrode caps. A Japanese model 75 kVA pedestal, alternating current waveform of spot welder, was engaged to carry out the welding processes up to 900 welding attempts on pneumatic system. Subsequently, it was converted into servo-based electrode actuating systems and repeated the entire welding processes. The carbon and stainless steel sheets are primarily used to weld in this experiment. The electrode caps are then sharpened by CDK-R dresser to remove the mushroom growth which has regularly been induced for every 400 welding attempts. As for the macrograph and micrograph observations, the electrode caps are measured for diameter growth of electrode caps as well as the copper-to-chromium ratio. The chromium content has been significantly reduced at the electro tip areas due to the direct expose of heat generation which becomes a regular phenomenon in both the systems. However, the results from servo-based system are deemed to be offering lower tendency of wear and tear factors when compared to the pneumatic-based system.
In this article, a comprehensive geometrical–mechanical–thermal predictive model is developed for thermal contact conductance between two flat metallic rough surfaces. The rough surface was characterized by Weierstrass–Mandelbrot fractal function. The micro-morphology was measured by laser microscope to identify the fractal parameters that were then applied to mechanical and thermal modeling. A new contact mechanics model was then proposed to calculate the contact parameters, and different contact scales between asperities and three modes of deformation, elastic, elastic–plastic and fully plastic, were taken into account. The normal contact pressure, which should be equal to the exterior load, was formulated as a function of the fractal parameters, the maximum contact area and the material physical properties of the given surface. Based on the contact mechanics model, first a single pair of contacting asperities was proposed and then multi-contacting asperities were combined to get total thermal contact conductance. The influences of contact load, surface roughness, asperity top radius and contact area as well as the temperature on the thermal contact conductance were investigated by using the proposed model. The investigation results showed that thermal contact conductance increases with the contact load and contact area. The larger the surface roughness, the smaller is the thermal contact conductance. Finally, the experiments were conducted to validate the effectiveness of the thermal contact conductance modeling. This geometrical–mechanical–thermal predictive model was compared with the two existing predictive models and a series of experimental data. The results showed good agreement, demonstrating the validity of the model and providing certainty for further study on the heat transfer between contact surfaces.
In minimally invasive neurosurgery, there is a gap between the need for a micro-burr hole to be opened on the skull to expose the enclosed brain for further operation and the proper technology available. Conventionally, a burr hole is generated by a drilling perforator, which usually causes damage to the vital soft tissue beneath skull. Besides, because of the extremely low mechanical strength of a micro-drilling bit, a micro-hole cannot be generated on the hard skull by the conventional drilling method. To bridge this gap, an ultrasonic vibration-assisted micro-burr hole forming technique has been developed in this study and its effectiveness has been proved through in vitro experiment on cat skull. With the assistance of ultrasonic vibration (29.7 kHz), a micro-hole has been successfully formed on skull with a 300 µm diameter conically tipped tool. Ultrasonic vibration of a large amplitude is found beneficial because the thrust force can be greatly reduced by increasing the vibration amplitude. Moreover, the micro-hole forming is free of cutting and chips. The ultrasonic vibration is found to have a hammering effect similar to shot peening, and a layer of dense tissue is formed around the hole and no chip is generated in the hole forming process. Besides, since the ultrasonic vibration tool can only fragment hard bone tissue without causing damage to the soft tissue beneath skull, a safe micro-hole forming technique can be enjoyed. Based on the findings from this study, a micro-burr hole perforator can be developed for the next-generation minimally invasive neurosurgery.
Ultrasonic-assisted turning is a machining process in which a vibrational displacement (usually in ultrasonic frequencies) is superimposed with the machining displacements in the cutting direction (one-dimensional ultrasonic-assisted turning) or in the cutting direction along with the radial direction (two-dimensional ultrasonic-assisted turning or elliptical ultrasonic–assisted turning). In this research, an elliptical ultrasonic–assisted turning tool is designed in ABAQUS software, in which the longitudinal and bending vibration modes have the minimum resonance frequency difference, so that the resonance of both the vibration modes can be achieved in a definite frequency. A set of half-ring piezoelectric stacks is employed for excitement of the bending mode, and a set of ring-shaped piezoelectric stacks is used for the excitement of the longitudinal mode. There is a phase shift with the amount of /2 between the longitudinal and bending vibration modes to produce an elliptical vibration. The manufactured tool is employed for machining of copper, which resulted in better surface finish and lower cutting forces.
This article presents a sensitivity analysis of residual stress based on the verified residual stress prediction model. The machining-induced residual stress is developed as a function of cutting parameters, tool geometry, material properties, and lubrication conditions. Based on the residual stress predictive model, the main effects of the cutting force, cutting temperature, and residual stress are quantitatively analyzed through the cosine amplitude method. The parametric study is carried out to investigate the effects of minimum quantity lubrication parameters, cutting parameters, and tool geometry on the cutting performances. Results manifest that the cutting force and residual stress are more sensitive to the heat transfer coefficient and the depth of cut, while the cutting temperature is more sensitive to the cutting speed. Large maximum compressive residual stress is obtained under a lower flow rate of minimum quantity lubrication, small depth of cut, and the proper air–oil mixture ratio. This research can support the controlling and optimization of residual stress in industrial engineering by strategically adjusting the application parameters of minimum quantity lubrication.
Today, die design standards are used to design the structure of die components. These standards are usually based on high safety factors. So, the die components are often heavier and larger than required. In this article, a software package is developed which can design an appropriate topology of body structure of stamping die components with a reduced weight. This is done by implementing the evolutionary structural optimization algorithm. The proposed structure can also be modified by the designer to accommodate for a simpler casting method. This software package is developed in Microsoft Visual C# programming environment with a link to Abaqus software to analyze the finite element simulation of the process. The operation of the software is demonstrated by an example where the die for a sheet metal part is studied. The die components are initially designed, analyzed and compared with the standard die (the die which is in general use today). The final results show a reduction of 37% of volume and 8% of maximum displacement, respectively.
An investigation into the cutting performance of newly developed free-cutting steels was conducted at high cutting speeds (150, 200 and 300 m/min) using cemented carbide cutting tools. The tool life, cutting force and surface roughness were measured to study the effect of the Mn/S ratio in weight percent on the cutting performance of the steel. The experimental results confirmed that the Mn/S ratio had a great influence on the machinability of the steel. It was more beneficial to form a MnS lubricant zone during the machining when the ratio is 3.33. The MnS lubricant zone formed on the rake face could reduce the tool wear and improve the tool life. A lower main cutting force could reduce the friction and bonding between the tool rake face and chip. The best machinability of the steel in terms of the tool life and main cutting force was obtained when the ratio was 3.33. The surface roughness decreased as the cutting speed increased when the Mn/S ratio was less than 3.33, and it increased when the ratio was greater than 3.33. The surface roughness of the steel also had a notable connection with the radial force. A properly high radial force could be beneficial in reducing the surface roughness because of the extrusion between the tool and the machined surface.
Titanium alloys generally show low machinability ratings. They are referred as difficult-to-cut materials due to their inherent properties such as low thermal conductivity, high chemical reactivity and high strength at elevated temperatures. Cooling strategies play an important role to improve the machining performance of the cutting process. In order to facilitate the heat dissipation from the cutting zone, generous amount of coolant is used when machining highly reactive metals such as titanium alloys. Generally, cutting coolants are nominated as pollutants due to their non-biodegradable nature. This article presents experimental evaluation of a minimal quantity cooling lubrication system. The study investigates a combination of sub-zero-temperature air and vegetable oil–based mist as possible environmentally benign alternative to conventional cooling methods. The results are compared with the dry and flood cutting environments as well. Machinability was evaluated experimentally by considering the surface finish, cutting forces, tool life and their associated tool wear mechanisms. It was concluded from the results obtained from the surface roughness, cutting force and tool life investigation that minimal quantity cooling lubrication (internal) cooling strategy has encouraging potential to replace the conventional flood cooling method.
Start-up energy consumption is a vital component of machine tool energy consumption. In some cases, such as forecasting and quota planning for energy consumption, the start-up energy consumption must be acquired before practical machining, so that the determination of start-up energy consumption before machining is indispensable. However, the start-up energy is usually neglected or regarded as a part of the no-load energy because its characteristics are complicated and unavailable by theoretical computing models. These treatments could result in significant errors under certain working conditions and could also undermine increasing the accuracy requirements for energy analysis. To close this gap, this article presents a method for determining start-up energy consumption based on specific databases consisting of data and functions. To use the database, the relative change in the rate of power is utilized to identify a start-up process, and a relation model between the start-up energy and the spindle speed is established. The energy consumed in the starting process is obtained by summing the energy consumption of each recording interval or by integrating the power function in its time domain. This experimental study proves that this approach has a relatively high accuracy. In addition, the analysis of its application shows that this method is practical for forecasting energy consumption of a start-up process, planning the energy quota for machining a piece of work in manufacturing and other purposes.
Gear shaping is a widely applied technology to produce spur gears. Generally, the pinion cutter and the gear workpiece rotate uniformly with a given gear ratio during the conventional gear shaping process, which can cause a large variation of the cutting area per stroke in cutting tooth spaces. It makes the cutting force less than the rated capacity of the gear shaper in most cutting strokes and thus reduces the process efficiency. To overcome such a shortage, a new spur gear shaping method is proposed in this article, in which the cutting area per stroke is homogenized to a target value through optimizing the circular feed rate. The new method can enhance process efficiency by keeping the cutting force equivalent to the rated capacity of the gear shaper. The specific algorithm includes a number of aspects: cutting area calculation, gear profile generation, cutting area analysis of conventional gear shaping, and cutting area homogenization. Additionally, the new spur gear shaping method is demonstrated and validated using a VERICUT simulation. From the simulation results, it is found that the process efficiency is improved up to 40% via the efficient gear shaping because of the reduced number of shaping strokes. Hence, the new spur gear shaping method is applicable for computer numerical control gear shapers to improve the process efficiency significantly without any additional hardware changes.
To cope with the problems of energy shortage and environmental pollution caused by the large number of retired cars, the energy efficiency of shredding recycled car bodies urgently needs to be improved. Before shredding, recycled car bodies are always cut into shaped metal plates and piled in several sheets like sandwich plates. Currently, the lightweight design philosophy has driven the widespread application of multi-materials in car bodies. In this study, the finite element and experimental methods are used to analyse the shredding process of multi-material plates from recycled car bodies in order to determine the characteristics of plates with different thicknesses and materials. The results showed that the shredding efficiency of steel laminates with less than three sheets is quite low although the efficiency can be raised by increasing the thickness. The shredding energy efficiency is higher for Al alloy laminates than for steels. The shredding energy efficiency can be improved by raising the strength of the shredding material. The results of this study proved that the shredding energy consumption can be reduced by shredding the different materials of the multi-material boards separately.
The use of curvilinear fibre paths to develop variable stiffness laminates is now recognised as a promising technique offering great potential for performance improvements over conventional ‘straight fibre’ laminates. Its manufacture is feasible by fibre placement technologies, such as automated fibre placement. However, these technologies present a set of limitations that need to be included in the design to guarantee the manufacturability and quality of the composite laminates. Although this approach experiences an increasing interest from the specialised literature, most of the works completed overlook the manufacturing reality and, as a result, variable stiffness laminates are not used in industry. This work aims to provide a review of the State-of-the-Art on design for manufacture of variable stiffness in order to highlight the current gaps and research needs. As a conclusion, tools for analysis of the effect of manufacturing defects, manufacturing optimisation of gaps/overlaps or cycle time and the systematic integration of manufacturing constraints in design, are the main challenges that will be faced in the future to be able to exploit the potential of this advanced tailoring technique.
The effect of strength and toughness on the weldability of high-strength steels is very vital consideration in the offshore oil and gas industries. Improved impact toughness of high-strength steels in offshore structures enables viable exploitation of hydrocarbons in technologically challenging conditions. This article reviews improvements in the weldability and impact toughness of high-strength steels. Steels with high strength are associated with high carbon content and addition of alloying elements as they induce hardness which leads to a higher risk of brittle fracture and hydrogen-induced cracking needs. The combination of high strength with high toughness was studied by examining the toughening mechanism of thermomechanical-controlled processing steels, which have higher strength than conventional steel plates but meet the conflicting requirements of strength, toughness and weldability. The thermomechanical-controlled processing production process entails controlled rolling process combined with accelerated cooling or direct quenching to ensure stable mechanical properties of thermomechanical-controlled processing products in welded constructions. It is concluded that due to their very fine grain size and refined heat-affected zone structure, thermomechanical-controlled processing steels can be an effective cost-saving means for fabrication of offshore structures, particularly in shipbuilding, offshore platforms and pipelines for high-operating pressures.
This article proposes the distribution similarity measure–based Gaussian mixtures model for the contact-state (CS) modelling in force-guided robotic assembly processes of flexible rubber parts. The wrench (Cartesian force and torque) signals of the manipulated object are captured for different states of the given assembly process. The distribution similarity measure–based Gaussian mixtures model CS modelling scheme is employed in modelling the captured wrench signals for different CSs. The proposed distribution similarity measure–based Gaussian mixtures model CS modelling scheme uses the Gaussian mixtures model in modelling the captured signals. The parameters of the Gaussian mixtures models are computed using expectation maximisation. The optimal number of Gaussian mixtures model components for each CS model is determined by considering the classification success rate as an index for the similarity measure between the distribution of the captured signals and the developed models. The optimal number of Gaussian mixtures model components corresponds to the highest classification success rate; hence, object elasticity variation would be accommodated by properly choosing the optimal number of Gaussian mixtures model components. The performance of the proposed distribution similarity measure–based Gaussian mixtures model CS modelling strategy is evaluated by a test stand composed of a KUKA lightweight robot doing peg-in-hole assembly processes for flexible rubber objects. Two rubber objects with different elasticity are considered for two experiments; in the first experiment, an elastic peg of 30 Shore A hardness is considered and that of the second experiment has hardness of 6 Shore A which is even softer than the one used in experiment 1. Employing the proposed distribution similarity measure–based Gaussian mixtures model CS modelling strategy excellent classification success rate was obtained for both experiments. However, more Gaussian mixtures model components are required for the softer one that gives a strong impression of the non-stationarity behaviour increment for softer materials. Comparison is performed with the available CS modelling schemes and the distribution similarity measure–based Gaussian mixtures model is shown to provide the best classification success rate performance with a reduced computational time.
Incremental forming is a method for rapid-prototyping and low-volume production. Incremental sheet metal hammering is relatively a new technique in which successive blows of punch on the clamped sheet are used to apply desired shape. In this article an incremental sheet metal hammering system has been designed and developed. The developed mechanism is equipped with a cam shaft including some hard metallic balls as dampers into the central driver core. It can reduce the system vibration to some degree. This research describes the theoretical, simulation and practical background of the designed system. In addition, experiments are accomplished to assess the tool performance. Also, by evaluation of experimental results, the effects of some parameters on the surface quality and maximum forming angle have been studied.
Variation in the geometric and surface features of segmented chips with an increase in the volume of material removed and tool wear has been investigated at cutting speeds of 150 and 220 m/min at which the cutting tools fail due to gradual flank wear and plastic deformation of the cutting edge, respectively. Among the investigated geometric variables of the segmented chips, slipping angle, undeformed surface length, segment spacing, degree of segmentation and chip width showed the different variation trends with an increase in the volume of material removed or flank wear width, and achieved different values when tool failed at different cutting speeds. However, the chip geometric ratio showed a similar variation trend with an increase in the volume of material removed and flank wear width, and achieved the similar value at the end of tool lives at cutting speeds of both 150 and 220 m/min regardless of the different tool failure modes. Plastic deformation of the tool cutting edge results in severe damage on the machined surface of the chip and significant compression deformation on the undeformed surface of the chip.
Servo presses have recently come into prominence for sheet metal forming operations due to their flexibility, controllability, and simplicity. Minimum energy consumption and maximum tool life are their significant characteristics, leading to considerable reductions in manufacturing costs. This article presents technological review on design and applications of servo presses. The characteristics of servo presses are described and compared to conventional and hydraulic presses. Mechanisms used in servo presses and their motion concepts are evaluated with design features. The industrial background of mechanisms is reported with typical examples from leading press manufacturers. A new classification of the servo presses is presented according to mechanisms and drivers. Besides, ranking of press types according to power control and mechanisms is determined. Servo presses with slider-crank mechanism design are preferred due to their distinctive characteristics.
Freeform complex surfaces have become an essential part of many devices to perform the required functions. Many of these components require nanometer-level surface finish to perform the desired functions efficiently. In this work, an attempt has been made to improve the external morphology of freeform surfaces, especially knee joint, by abrasive flow finishing process. A uniform mirror finished surface with improved finishing rate is achieved for stainless steel knee joint. Extrusion pressure is varied to reduce final surface roughness value and finishing time. Experimentally, good surface finish ranging from (Ra) 42.9 to 62.5 nm is achieved at various locations of the knee joint which are within the recommended American Society for Testing and Materials standard (100 nm) of knee joint prosthesis. Effects of abrasive flow finishing process parameters are investigated to develop "know how" of the process on the freeform surfaces. Abrasive flow finishing process has given 76.56% reduction in finishing time as compared to the time required by "ball end" type tool used for finishing knee joint.
Geometric features of the segmented chip have been investigated along with the volume of material removed at a cutting speed at which tool wear is characterized by the gradual development of flank wear when cutting Ti-6Al-4V alloy. The chip geometric variables varied with an increase in the volume of material removed as the combined effect of change in tool’s geometry and increase in cutting temperature. Plastic deformation dimples were observed as periodical regions on the machined surface, a row on each undeformed surface and region on the top of the slipping surface of the segmented chip when cutting with new tool; these dimples on the undeformed surface and machined surface are elongated in the direction of chip flow. All these dimples became less with an increase in the volume of material removed and almost disappeared when the chip was removed with the worn tool at the end of its life. A model of segmented chip formation process has been proposed to satisfactorily explain the formation of the plastic deformation dimples on the undeformed surface and machined surface of the segmented chip produced with a new cutting tool and the transition of chip geometry with the evolution of tool wear.
Nickel-based Inconel X-750 superalloy is widely applied in aerospace industry and manufacturing of gas turbine blades, power generators and heat exchangers due to its exclusive properties. As a consequence of low heat transfer coefficient and work-hardening properties, this alloy is known as a poorly machinable alloy. In this work, effect of machining parameters (cutting speed, feed rate and depth of cut) on cutting forces and surface roughness was investigated during turning of Inconel alloy X-750 with coated carbide tool. In order to meet the demands of the environment-friendly cutting processes and human health, biodegradable vegetable oil (BioCut 4600) was selected as the cutting fluid. The results were analyzed using response surface methodology and statistical analysis of variance, and mathematical models for cutting forces and surface roughness were proposed. Results indicated that feed rate and cutting speed were the most effective parameters on the surface roughness. However, depth of cut was the most effective parameter on cutting forces in comparison with cutting speed and feed rate. Eventually, in order to achieve the main aims of industrial production in large amounts and green manufacturing, the ranges for the best cutting conditions were presented.
Recently, tubular-type coupled torsion beam axle, which is a component of the automotive rear suspension systems, has been developed by using ultra-high strength steel. It is manufactured by hot stamping process to enhance the strength and reduce springback. The hot stamping process is classified as a direct method and an indirect method according to forming sequence and quenching method, so-called die quenching or water quenching. Each of these methods has limitations in the aspect of dimensional accuracy and strength. Hybrid quenching is a new quenching method which sprays water to the tube directly in addition to die quenching. In this study, direct hot stamping with hybrid quenching was applied to produce an automotive tubular coupled torsion beam axle of ultra-high strength steel. This study proposes a simulation method of hybrid quenching for tubular beam and the hybrid quenching method was evaluated experimentally. Finally, the proposed hybrid quenching method has been found very effective in reducing the cooling time and thermal deformation.
The microwave curing of composites is a promising technology to manufacture the composite components faster than conventional thermal curing. But how the shortened temperature profiles, which determine the duration of microwave curing processes, will affect the outcome of cured parts is still not clear. In this study, the effects of microwave curing processes governed by different temperature profiles on the mechanical properties of carbon fibre–reinforced composite material have been experimentally investigated. The results showed that microwave-cured composites have similar curing kinetics as the conventional thermally cured ones, and they were better in interlaminar shear and flexural strengths than thermally cured ones, while slightly lower in tensile and compressive strengths. The increase in heating rates in the temperature profiles enhanced the compressive and flexural strengths of the composites within a certain range, but moderately compromised the tensile and interlaminar strengths; the reduction in holding time can decrease the mechanical performances of the composites moderately, except for the interlaminar shear strength. The micrographs of the fracture surfaces after the interlaminar shear tests demonstrated the enhancing effect of microwave curing on the fibre–matrix interfacial bonding, but this effect can be slightly compromised when increasing the heating rates. These results could serve for the tradeoffs between reducing the manufacturing time and preserving the mechanical properties of the microwave-cured composites.
In recent years, condition-based maintenance has been increasingly considered for improving system reliability and cost effectiveness. Equipment hazard rate prognosis plays an important role in condition-based maintenance scheduling. Thus, this article focuses on evaluating and extracting environment factors that reflect environmental effects on the equipment hazard rate. Better condition-based maintenance schedules can be designed through the use of equipment hazard rates considering environmental influences. An innovative methodology is proposed in this article: first, statistical pattern recognition is used to extract environment factors; a method combining rough sets and an analytic hierarchy process is used to obtain the different weighting factors for the different environmental elements, and then they can be used to extract future environment factors; and finally, the environment factors are dynamically applied in an improved condition-based maintenance model. The results of a case study show that this methodology can be used to develop comprehensive and optimal maintenance schedules. Furthermore, compared with traditional models, the improved model is proved to be more effective and realistic because of the evaluation and application of environment factors.
As for the gantry-type machine tools, the forces of the slide blocks supporting the beam are different for different saddle locations, which would further affect the stiffness of the slider–guide joints and the dynamic characteristics of the whole machine tools. Therefore, the beam kinematic joints (the slider–guide joints) on the gantry-type machine tools are crucial for the dynamics prediction of traveling bridge systems. In this article, considering the effect of axis coupling force on the slider–guide joints’ stiffness, an equivalent dynamic model of traveling bridge systems for the gantry-type machine tools is established using hybrid element method. The additional load variation in the four slider blocks is analyzed for different locations of the saddle, and the variation in the slider–guide joints’ stiffness and traveling bridge system natural frequency are also studied. Finally, validation experiments are conducted on the traveling bridge systems of the gantry-type milling machine tools, and the results show that the dynamic modeling proposed in this article can reach a higher accuracy.
The use in motor vehicles of lightweight metals such as aluminium and titanium provides a high strength-to-weight ratio, thereby lowering overall weight and reducing energy consumption and CO2 emissions. Aluminium alloys have thus become an important structural material especially high strength and ultra-high strength alloys such as AW 7020. Many studies have shown that the presence of an aluminium oxide (Al2O3) thin film formed naturally on aluminium alloys is detrimental to welding. This article further investigates the specific effect of the Al2O3 thin film on welding AW 7020 alloy. An analytical experiment of welded AW 7020 alloy using a pulsed metal inert gas (MIG) robotic weld machine is carried out. Four specimens were cut, butt welded, and examined. The weld parameters included pre-weld cleaning of the Al2O3, pre-, and post-weld heat treatment. Al2O3 was removed by wire brushing; preheating was conducted at a temperature of 130 °C; and natural ageing was conducted by post-weld heating at 480 °C for 2 h, followed by quenching in water at 90 °C for 8 h, reheated, and sustained at 145 °C for 15 h. The result shows that the presence of Al2O3 layer appears not to be detrimental to the weld with new welding technologies, therefore suggesting that it is not necessary to grind off the Al2O3 layer before welding. This finding implies that welding costs can be lowered and weld quality improved when new welding technologies are applied in the welding of high-strength aluminium alloys.
Edge effect is unavoidable in polishing process when the polishing pad passes by the workpiece edge, which influences the entire form accuracy of free-form surfaces of optical components in computer-controlled polishing, or even reduces their effective aperture. This article focuses on a theoretical and experimental investigation into the material removal influenced by edge effect for polishing along a certain path. The contact pressure distribution models for polishing the workpiece edge are summarized and modified into four representative models: linear model, skin model, linear skin model and divided skin model, which are adopted to calculate the theoretical material removal profiles orthogonal to the straight or curved polishing path, in this article. So, the material removal models are built in the process of polishing along tool path instead of polishing on a single point. And experiments are carried out to choose the most suitable contact pressure distribution model according to the comparison of experimental profiles and the different theoretical profiles. Experimental results reveal the influences of edge effect on material removal and a modified parameter is introduced into the theoretical material removal profile for the curved path to coincide with the experimental profile better. In addition, some qualitative analyses about how to reduce the edge effect are also given in this article.
Economies of scale, globalization and mass production have pushed the scale of manufacturing processes and the ability to compete beyond the scope of most small and medium enterprises. With the affordability of standard, off-the-shelf industrial and computer numerical control components, software and allied tools, we investigate a systematic model that looks at a number of possible ways of downscaling machines and operations that are of particular relevance to small and medium enterprises. The concepts presented here specifically deal with understanding dependencies and scale factors in complex systems, where the design is realized on the basis of commercial "off-the-shelf" components and subsystems commercial off-the-shelf). It is systematically integrated into proven design methodologies such as the Verein Deutscher Ingenieure V-models, axiomatic design and quality function deployment.
Despite significant advances in modelling and design, mechanical systems almost inevitably fail at some point during their operative life. This can be due to a pre-existing design flaw, which is usually overcome in a revision, or more commonly due to some unexpected damage during operation. To overcome a failure during operation, a new method in designing machines or systems is proposed that creates a result, that is, resilient to both expected and unexpected failure. By shifting the focus from a detailed assessment of the underlying cause of failure to how that failure will manifest, a system becomes inherently resilient against a wide range of failure modes. The proposed process involves five steps: cause, detection, diagnosis, confirmation and correction. This is demonstrated with an application to a generic 4 bar linkage mechanism. Through this process, the system is able to return to a near perfect state even after a permanent deformation occurs in the mechanism. These results show the potential that this self-repairing design process has applications including robotics, manufacturing and other systems.
The article aims to show that the electrical discharge machining plasma can be developed in solid or gaseous medium, through the numerical and experimental evaluation of process performance. The plasma channel developed in gaseous medium is based on an electrical discharge developed in a gas bubble and the plasma channel developed in solid medium is based on underwater explosions. The main electrical difference between both mediums is on its electrical resistivity. However, if the radius of plasma channel increases, its electrical resistivity should decrease because its electrical resistance and applied current intensity are constant, or in other words, the applied electrical power is constant during discharge duration. Thus, the plasma channel is developed in gaseous and solid mediums, with same electrical resistivity and Joule factor, because the radius of plasma channel is considered constant during discharge duration. The comparison of numerical results of electrical discharge machining performance obtained through an electrical discharge machining plasma developed in gaseous and solid mediums shows high agreement with the experimental results. Therefore, the electrical discharge machining plasma developed in solid and gaseous mediums is reliable when hydrocarbon oil is used as a dielectric fluid due to the high degree of agreement of numerical and experimental results of electrical discharge machining performance.
In this study, the two geometry tools, including straight cylindrical pin and upward conical pin, are used to create channel in monolithic plate of Al 5083 alloy using the modified friction stir channeling technique. The channeling process was done under different directions including linear and non-linear channeling paths. Using upward conical pin caused easy channeling under non-linear paths, increase in height and hydraulic diameter of channel, and improvement in channel structure. As a result, in modified friction stir channeling technique using both tools, the shape of channels was stable and constant along the different channeling paths. However, the channel size was changed along the different paths. Along the vertical and straight paths, the characteristics of channel were stable and constant during the channeling process. Existing results were also achieved along the curve direction when the advancing side was along the inner curve. Nevertheless, when the advancing side was along the outer curve, the values of channel characteristics were varying at the various locations of the curve path. The stop-action technique and observations on the cross section of channels were utilized to explore the variations of channels and the channeling mechanisms along different paths. It was found that the variations of channel properties were because of the location of the displacement of shear layers along curve and the amount of extracted material by tool pin along the curve paths.
Friction stir processing is a novel material fabrication technique. This study was undertaken in order to investigate a suitable set of friction stir processing parameters to form AL7075T651/TiN nano composite. A number of samples were produced by varying the process parameters, namely, tool-pin geometry, number of passes and the direction of tool rotation. The pin geometries employed include triangular, square and threaded taper; the passes were varied over two levels (i.e. 2 and 4) and the tool rotation was changed as clockwise and counter clockwise between the successive passes. The effect of these variations on the composite was quantified through several microstructural and mechanical tests. The increase in the number of passes was observed to improve various characteristics of the composite (i.e. distribution of TiN particles, grain refinement and mechanical properties). The effect of tool geometry, however, was associated with the choice of the number of passes. The change in the direction of tool rotation between the consecutive passes was witnessed to improve the distribution of TiN particles. From the X-ray diffraction analysis of the samples, the formation of several new phases was detected. These were found to have effect on the mechanical properties of the composite. A good trade-off among various properties of the composite (i.e. hardness, tensile strength and ductility) was realized when the friction stir processing was performed using square tool and employing four passes with simultaneously changing the direction of tool rotation between the successive passes. This study is the first report on the fabrication of AL7075T651/TiN nano composite through friction stir processing route.
Customer requirement analysis has become a primary concern for companies who compete in the global market. Kano’s model, as a customer-driven tool, has been widely used for customer requirement analysis in product improvement. Although a number of authors have improved the traditional Kano’s model, there has been a limitation of dealing with the fuzzy and uncertainty of human thought under multi-granularity linguistic environment. Furthermore, the traditional Kano’s model faces problems regarding quantitative data computation and customer requirements importance assessment. In this article, an improved fuzzy Kano’s model is proposed to analyze customer requirements under uncertain environment. A 2-tuple linguistic fuzzy Kano’s questionnaire is developed to model the uncertainty and diversity of customers’ assessments using 2-tuple linguistic variables under multi-granularity linguistic environment. Then, a comprehensive and systematic methodology is presented to prioritize customer requirements through quantitative analysis of improved fuzzy Kano’s model. This method integrates subjective judgments assigned by decision maker, objective weights based on maximizing deviation method and customer satisfaction contribution to determine the priority ratings of customer requirements. A case study of combine harvester development is presented to evaluate the proposed model.
The production control of failure-prone manufacturing systems is notoriously difficult because such systems are uncertain and non-linear. Since the introduction of hedging-point policies, many researches have been done in this field. However, there are few literatures that consider the production control problem of tree-structured manufacturing systems. In this article, a hedging-point production control policy is proposed for a multi-machine, tree-structured failure-prone manufacturing system. To obtain the optimal hedging points, an iterative learning algorithm is developed by considering the system’s characteristics. A simulation method is embedded in the iterative learning algorithm to calculate the system cost. To estimate the performance of the proposed algorithm, comparisons are made between our algorithm, genetic algorithm and particle swarm optimization algorithm. The experimental results show that our algorithm works better than others in reducing the computation time and minimizing the production cost.
A three-dimensional molecular dynamics model is presented for the simulation of the creation of a micro-hole on a thin film metal substrate via laser ablation. For the presented analysis, molybdenum and aluminium specimens are selected and short pulses are assumed. The laser fluence takes several values between 0.5 and 20 J/cm2. The proposed models include significant laser ablation phenomena such as plasma shielding. However, they are not computationally intense. In this study, the Morse potential is used for the interactions of the atoms of the specimens. The analysis is carried out in order to investigate the ablation rate, the ablation depth and the mean temperature of molybdenum and aluminium targets under their heating by the laser beam, for several different values of fluence. Results for molybdenum indicate that as fluence increases, it takes less time for the atoms to be ablated. For low-fluence pulses, more than one pulse may be required for the ablation of all atoms. For high-fluence pulses, the ablation is not uniform across the entire duration of the pulse and the specimen is overheated. A fluence value around 2–3 J/cm2 is suggested for uniform ablation. From the analysis, it is evident that the evolution of ablation and system temperature is different for molybdenum and aluminium, for the same laser fluence. This is attributed to different crystalline structures and absorptivity of each material. It may be said that molecular dynamics prove to be a powerful tool for the simulation of nanomanufacturing processes and useful conclusions are drawn from the analysis.
Tube hydroforming is a process that uses internal pressure and axial feeding simultaneously to form a tube into a desired shape. The internal pressure provides the stress required to yield the material while axial feeding eases metal flow helping to produce a part without wrinkles and with even wall thickness. Pulsating pressure hydroforming applies loading path with fluctuating pressures. In this study, pulsating pressure hydroforming of T-joint part was examined experimentally. Six process parameters in pulsating pressure loading path were selected. Using Taguchi design of experiments with six parameters and two levels for each parameter, 12 experiments were conducted to study the effects of pulsating pressure parameters on the parts’ defects and shape accuracy. Signal-to-noise ratio and analysis of variance were employed to determine the important process parameters affecting the final part in terms of wrinkling, bulge height and wall thickness. Three linear regressions without any interaction between the parameters were extracted for three quality responses and were evaluated through three extra experiments that show the best levels for three responses. The results show reasonable agreement between the experiments and linear regression models.
Technology-centric products often contain parts, software, and materials that have procurement lives that end before the product they are in reaches the end of its life cycle. Life-cycle mismatches between parts and products, which is referred to as obsolescence, can result in large life-cycle costs for mission, safety, and infrastructure critical products, such as aircraft, medical, and military systems. Diminishing Manufacturing Sources and Materials Shortages is a type of obsolescence that describes the loss of the ability to purchase (or procure) a part (or its associated technology) from its original manufacturer. A key enabler for performing pro-active and strategic management of the life cycle of mission, safety, and infrastructure critical products is the ability to forecast when technologies and parts will become unavailable for purchase, that is, obsolete. This article reviews methods that are used to forecast obsolescence, focusing on long-term forecasting used to predict the obsolescence dates for technologies and electronic parts.
An attempt has been made to apply the Taguchi parameter design method and multi-response optimization using desirability analysis for optimizing the cutting conditions (cutting speed, feed rate and depth of cut) on machining forces while finish turning of AISI 4340 steel using developed yttria based zirconia toughened alumina inserts. These zirconia toughened alumina inserts were prepared through wet chemical co-precipitation route followed by powder metallurgy process. The L9 (4) orthogonal array of the Taguchi experiment is selected for three major parameters, and based on the mean response and signal-to-noise ratio of measured machining forces, the optimal cutting condition arrived for feed force is A1, B1 and C3 (cutting speed: 150 m/min, depth of cut: 0.5 mm and feed rate: 0.28 mm/rev) and for thrust and cutting forces is A3, B1 and C1 (cutting speed: 350 m/min, depth of cut: 0.5 mm and feed rate: 0.18 mm/rev) considering the smaller-the-better approach. Multi-response optimization using desirability function has been applied to minimize each response, that is, machining forces, simultaneously by setting a goal of highest cutting speed and feed rate criteria. From this study, it can be concluded that the optimum parameters can be set at cutting speed of 350 m/min, depth of cut of 0.5 mm and feed rate of 0.25 mm/rev for minimizing the forces with 78% desirability level.
This article demonstrates implementation of immersed boundary method in continuous casting simulation involving boundary movement. In this methodology, the immersed boundary method is coupled with the second-order accurate finite difference solution of unsteady three-dimensional heat conduction equation. The moving molten metal front is modelled using the immersed boundary method in a Cartesian mesh framework that provides simplicity in its implementation and reduces the computational time as compared to the adaptive mesh solutions. A parallel programming paradigm using message passing interface has been implemented to obtain enhanced computational efficiency. This study has focused on capturing moving boundary during continuous casting and predicts the temperature distribution and shell thickness under different cooling ambiences and casting function. Good agreements with published data and correlations are obtained through numerical analysis. Mould-region shell thickness agrees well with Chipman–Fondersmith correlations. A new correlation has been further proposed for the delay constant at different heat extraction rates. The effects of key parameters like casting speed, convection and radiation from the continuous casting are also quantified in attempt to avail the data for optimal design of continuous caster.
Cutting parameters and material properties have important effects on the quality of milled surface, which can be characterized by fractal dimension and surface roughness. The relationships between two surface parameters (surface roughness and fractal dimension) and material hardness, elongation, spindle speed and feed rate were investigated, respectively, in this study. Four carbon steels, that is, AISI 1020, Gr 50, 1045 and 1566, were milled with five spindle speeds and four feed rates on a computer numerical control machine. The surface topographies were measured with a three-dimensional profiler. The surface profiles were obtained by re-sampling the data points on the surface topography in the measurement direction. The surface roughness and fractal dimension were calculated from the two-dimensional profiles, where the fractal dimension was obtained by the root-mean-square method. The results showed that for specific spindle speed and feed rate, the roughness of the milled surface decreased with the workpiece hardness, whereas the elongation and fractal dimension increased with the hardness. Based on the material hardness and elongation, spindle speed and feed rate, empirical formulae were established to quantitatively estimate the surface roughness and fractal dimension. Moreover, the spindle speed and feed rate can be easily calculated from the empirical formulae to achieve a surface with the desired surface roughness and fractal dimension. The empirical formulae have been demonstrated with the experiments and were shown to be applicable in estimating the surface roughness and fractal dimension for all carbon steels in end milling. The results are instructive for the fractal dimension estimation of the machined surfaces of carbon steel, which has not been previously studied.
Abundant application of cutting fluids may increase production cost and cause environmental and health damages, particularly when not properly managed. Thus, alternative measures are needed to overcome the difficulties of using cutting fluids. If sustainable and ecological manufacturing aspects are envisaged, any attempt to improve the machinability of such difficult-to-machine material is always welcome. In this direction, this research work aims to develop experimental set-up as a possible approach to fostering sustainability in metal cutting lubrication to supply solid lubricant at minimum quantity and also to study the effect of applying solid lubricant (molybdenum disulphide and graphite) mixed with oil, during turning of Inconel 718 using cemented carbide tools. The concentration of the solid lubricant in the fluid and the flow rate of the mixture were varied to analyse the main output parameters such as surface roughness, cutting forces and tool life. Experimental findings of this study show that minimum quantity solid lubricant consisting of molybdenum disulphide and oil mixture performed better, and therefore, it may be considered to be a cost-effective and environmental-friendly lubrication technique than flood coolant and sprayed oil with or without graphite to retard all types of damaging processes and to improve machinability characteristics of Inconel 718.
Ultrasonic consolidation has been shown to be a viable metal-matrix-based smart composite additive layer manufacturing process. Yet, high quantity fibre integration has presented the requirement for a method of accurate positioning and fibre protection to maintain the fibre layout during ultrasonic consolidation. This study presents a novel approach for fibre integration during ultrasonic consolidation: channels are manufactured by laser processing on an ultrasonically consolidated sample. At the same time, controlled melt ejection is applied to aid accurate fibre placement and simultaneously reducing fibre damage occurrences. Microscopic, scanning electron microscopic and energy dispersive X-ray spectroscopic analyses are used for samples containing up to 10.5% fibres, one of the highest volumes in an ultrasonically consolidated composite so far. Up to 98% of the fibres remain in the channels after consolidation and fibre damage is reduced to less than 2% per sample. This study furthers the knowledge of high volume fibre embedment via ultrasonic consolidation for future smart material manufacturing.
The main aim of this study is to produce new powder metallurgy (PM) Cu-B4C composite electrode (PM/(Cu-B4C)) capable of alloying the recast workpiece surface layer during electric discharge machining process with boron and other hard intermetallic phases, which eventually yield high hardness and abrasive wear resistance. The surface characteristics of the workpiece machined with a PM/(Cu-B4C) electrode consisted of 20 wt% B4C powders were compared with those of solid electrolytic copper (E/Cu) and powder metallurgy pure copper (PM/Cu) electrodes. The workpiece surface hardness, surface abrasive wear resistance, depth of the alloyed surface layer and composition of alloyed layers were used as key parameters in the comparison. The workpiece materials, which were machined with PM/(Cu-B4C) electrodes, exhibited significantly higher hardness and abrasive wear resistance than those of machined with the E/Cu and PM/Cu. The main reason was the presence of hard intermetallic phases, such as FeB, B4C (formed due to the boron in the electrode) and Fe3C in the surface layer. The improvement of the surface hardness achieved for steel workpiece when using PM/(Cu-B4C) electrodes was significantly higher than that reported in the literature. Moreover, the machining performance outputs (workpiece material removal rate, electrode wear rate and workpiece average surface roughness (Ra)) of the electrodes were also considered in this study.
Contrary to the conventional serial kinematics machine tools, the parallel kinematics machine tools exhibit nonlinear behavior which is a major source of the machining error. This causes even a linearly programmed path to be traversed along a nonlinear path. The resulting error, known here as the kinematic error, should be critically considered during the toolpath planning. The estimation of the maximum kinematic error using the concept of median osculating circle is introduced in this article. The proposed formulation demonstrates that the maximum kinematic error depends on the curvature of the actual trajectory. In order to estimate the curvature, constant curvature contour maps are introduced. These maps depend on the structural parameters of the machine and are recommended to be provided by the machine’s manufacturer. The constant curvature contour maps are illustrated to be an effective graphical tool for kinematic error estimation and thus successfully conducting the optimal planning of the toolpath and the workpiece setup. Consequently, it is recommended in this article that the constant curvature contour maps be employed in the format of a database by computer-aided manufacturing systems during toolpath planning and by interpolators during command generation or by a part programmer to optimally setup the workpiece or conduct the toolpath planning such that the least kinematic error occurs during the machining.
This article presents a topological technique for evaluating the performance of a hybrid flow-shop production system. Such a production system is modeled as a hybrid production network; each workstation of the hybrid production network has stochastic capacity levels. This article evaluates the probability of demand satisfaction as a performance indicator for the hybrid production network, in which the network has multiple lines and each workstation has a distinct defect rate. First, a topological transformation is utilized to transform a hybrid flow-shop production system into a network-structured hybrid production network; then, the hybrid production network is decomposed into several routes for flow analysis. Second, two procedures for two models (Model I considers the hybrid production network with parallel lines, Model II with intersectional lines) are designed to generate the minimal required capacity for workstations to satisfy the given demand. The probability of demand satisfaction is subsequently evaluated in terms of the minimal required capacities by applying the recursive sum of disjoint products algorithm.
The principle objective of this work is to present a methodology to evaluate the correlation between burr size attributes (thickness and height) and information computed from acoustic emission and cutting forces signals. In the proposed methodology, cutting force and acoustic emission signals were recorded in each cutting test, and each recorded original acoustic emission signal was segmented into two sections that correspond to steady-state cutting process (cutting signal) and cutting tool exit from the work part (exit signal). The dominant acoustic emission signal parameters including AEmax and AErms were computed from each segmented acoustic emission signal. The maximum values of directional cutting forces (FX, FY and FZ) were also measured in each trial. The experimental verification was conducted on slot milling operation which has relatively more complicated burr formation mechanism than that in many other traditional machining operations. Among slot milling burrs, the top-up milling side burrs and exit burrs along up milling side were largest and thickest burrs which were studied in this work. To evaluate the correlation between signal information and burr size, the computed signal information (5 parameters) and their interaction effects (10 parameters) were used to construct the input parameters of the multiple regression fitted models. Statistical methods were then used to assess the adequacy of individual input parameters and signal information. Using the acoustic emission and cutting force signals information in the input layer of multiple regression models, a high correlation was observed between the predicted and observed values of burr size. It was exhibited that due to complex burr formation mechanism in milling operation and strong interaction effects between cutting process parameters, no systematic relationship can be formulated between the milling burrs.
Binding of metal powders using electrochemically deposited binders provides a novel approach to achieve metal additive manufacturing at ambient temperature. In this study, using an in-house built experimental setup, a single layer of copper powders were electrochemically bound together with the help of nickel binder and the deposits were studied by scanning electron microscope and energy-dispersive X-ray spectroscopy. Mechanical characterization performed on the deposits reveals that the yield strength of the deposit is comparable to that of laser-sintered parts made from Cu/Ni powder. Furthermore, Taguchi studies have been conducted to investigate the optimal process parameters required for minimum diameter of electrochemically bound spot, layer thickness and yield strength. Analysis of variance and signal-to-noise ratio were used to determine the important levels of process parameters and the results were then experimentally verified.
Bulk residual stress of component originating from material preparation processing has an impact on large-scale assembly deformation and consequently affects dimensional and shape accuracy of assembly especially for those thick and asymmetric components. This article proposes a quantitative variation propagation modeling method, highlighting the subsequent impact of initial residual stress in raw material, and provides an effective pattern mapping method between bulk stress fluctuation and overall component or assembly deformation. The basic analysis approach considering residual stress is validated by test experiments previously. Legendre polynomials and Spline functions are employed to represent stress perturbation pattern and localized deformation pattern, respectively. Variation propagation is modeled in a case study of the horizontal stabilizer assembly system based on these non-linear mathematical representations. The orthogonal test is designed utilizing finite element analysis to simulate principal stress component perturbation. Corresponding regression analysis aimed at the optimized geometric target is conducted leading to confined Legendre coefficients range for better match. The mapping relation is developed graphically between Legendre coefficient’s pattern and Spline coefficient’s pattern revealing the region of influence and offers assembly deformation prediction as well as practical component selection suggestion for better match. The downstream quality control can be further traced back to the parameter setting of material preparation processing like stretch ratio. The methods we present help systematically improving compliant assembly precision in consideration with residual stress factor in aircraft assembly structure.
An integrated model based on finite-element method has been proposed to examine the mechanical and thermal responses of strips and work-rolls in tandem and reverse cold rolling operations. The model has been developed such that the influence of various process parameters, such as lubrication, rolling speed, frictional state and back-up rolls, can be examined. Thermal behaviors of the rolled material and the work-rolls have been analyzed using stream-line upwind Petrov–Galerkin approach, in order to make the model applicable to high-speed rolling processes, as well. The results have been compared to the actual on-line measurements and shown to be of acceptable accuracy. Such modeling approach can be considered as a useful means, providing a detailed insight on the thermo-mechanical response of strips, as well as work-rolls, during high-speed cold rolling of steel strips. Additionally, special attention has been drawn towards the prediction of the occurrence of the metallurgical phenomenon dynamic strain aging based on the results obtained from the numerical modeling in this work.
Fixture layout optimization is a procedure to optimize position of locators and clamps in order to minimize specified objectives. Deformation of workpiece is a serious problem of concern while designing a fixture. Proper positioning of fixture elements is indispensable to achieve desired machining accuracy, better surface finish and high productivity. In this work, a novel methodology is proposed that incorporates full factorial design of experiments and statistical analysis. Furthermore, the stability of the workpiece is ensured prior to the prediction of objective function. The result of the proposed technique is compared with the results of the genetic algorithm–based optimization technique. A case study has been considered to evaluate the proposed methodology. The objective function determines maximum elastic deformation of the workpiece during the entire machining process. Finite element method is used to formulate the objective functions. The constraints are natural frequency of the workpiece–fixture system and reaction forces. Besides, artificial neural network–based model is developed to predict the elastic deformation of the workpiece–fixture system within the range of design parameters.
In this article, the authors have attempted to use altogether a new hybrid machining process for making the holes in nickel-based superalloy (nimonic alloy) aerospace material and termed it as electro-discharge diamond drilling process. To perform this experimental study, they self-designed and developed a setup which is capable to hold as well as rotate the metal-bonded diamond abrasive tool electrode. They installed this setup on a ZNC 320 sinking electrical discharge machining machine and conducted the experimental study. The effects of input parameters such as gap current, pulse-on time, duty factor and tool rotation on the response parameters such as average surface roughness (Ra ) and average circularity (Ca ) of the drilled hole have been studied. It is observed that electro-discharge diamond drilling process has substantive effects on the improvement of Ra as well as on Ca in comparison to the hole made by stationary electrode electrical discharge machining (die-sinking electrical discharge machining) process. The photographs and micrographs of few selected workpieces were taken by metallurgical microscope and scanning electron microscope, respectively, which commensurate with the findings of the research study.
It is crucial to properly design the fixturing layout described by fixturing parameters, such as the fixturing sequence, the placement of clamping force, the locator position, and so on. This is because the clamping deformation of the thin-walled workpiece can influence extremely the machining accuracy and surface quality. Generally speaking, the finite element method can be used to easily obtain the deformation rule of the workpiece caused by one single fixturing parameter. But it is difficult to reveal the relationship between the multiple fixturing parameters and the clamping deformation of workpiece. Therefore, the workable finite element model of multi-fixturing layout is above all established for the thin-walled workpiece. Thus, clamping deformations can be calculated to be the training samples of the neural network. Next, according to the training samples, the prediction model is suggested for obtaining the clamping deformation from multiple fixturing parameters. When the prediction errors are defined as fitness function, the genetic algorithm is developed to search the optimal initial weights and thresholds for the neural network. The optimized neural network has better generalization and prediction ability than the non-optimized one. Ultimately, the embedded optimal model with the objective of minimizing the clamping deformation is presented for a multi-fixturing layout. When the individual fitness of each generation is constructed as a function of the clamping deformations, the genetic algorithm can be skillfully used to solve the embedded optimal model. Moreover, the experiment is conducted to validate the prediction method with good agreement between the predicted results and the experimental data. The above presented "analysis—prediction—control" method of clamping deformation not only improves the calculation efficiency of clamping deformation but also provides a basic theory of fixturing layout design for the thin-walled workpiece.
Turning by electrical discharge machining is an emerging area of research. Generally, wire-cut electrical discharge machining is used for turning because it is not concerned with electrode tooling cost. The process variant die-sinking electrical discharge machining can also be effectively used to generate free-form cylindrical geometries on difficult-to-cut materials with complex shapes at both macro and micro levels. The machining performance of electric discharge machine is defined and influenced by its process parameters, which significantly affects production rate and the quality of machined component. Thus, it is very important to select machining parameters and their levels cautiously in order to improve the outcome of the process. In this article, the authors have reviewed the research work carried out in the area of electrical discharge turning in the last decade for the improvement of material removal rate, surface integrity and roundness. In this review, various techniques reported by electrical discharge machining researchers on turning have been categorised in different electrical discharge machining variants. The article also discussed the future direction of research work in the same area.
For years, there have been tremendous endeavors to reduce makespan in an attempt to decrease the production expenses. This investigation aims to develop a scenario-based robust optimization approach for a real-world flow shop with any number of batch processing machines. The study assumes there are some uncertainties associated with processing times as well as size of jobs. Each machine can process multiple jobs simultaneously as long as the machines’ capacities are not violated. In order to verify this developed model and to evaluate the performance of the proposed robust model, a number of test problems are prepared and a commercial optimization solver is adopted to solve these test problems. For the purpose of validating the results, the robust model and mean-value model are carried out by simulation, which confirmed the proposed model.
The exponential growth of cross-enterprise collaboration in recent years has facilitated the emergency of a new manufacturing mode called social manufacturing, wherein order winning hinges mostly on their customer and demand-oriented manufacturing service capability rather than the traditional factors such as relationships and distances. Therefore, a manufacturing service capability estimation model is proposed in this article, which comprises two sub-models, that is, a machining service capability (M-capability) model and a production service capability (P-capability) model. The former explains what kinds of manufacturing service a manufacturing system can provide, while the latter estimates how much manufacturing service the manufacturing system can produce in a certain time period. Besides, each of the two sub-models is considered from both single-socialized manufacturing resources and multi-socialized manufacturing resources’ manufacturing system perspectives. First, an ontology and Semantic Web–based model is established for estimating the M-capability of a single-socialized manufacturing resource manufacturing system and further extended to multiple socialized manufacturing resources manufacturing systems. Then, P-capability evaluation model based on rough set–based propagation neural network is proposed for a single-socialized manufacturing resource manufacturing system. Afterward, the results of rough set–based propagation neural network are further utilized as the inputs of the latter particle swarm optimization–based P-capability estimation model for multiple socialized manufacturing resources manufacturing systems. Finally, a typical case is fully studied to illustrate the feasibility of the proposed models.
In order to break through the limitation of traditional axisymmetric spinning, a discretization method is made to form an oblique cone by die-less shear spinning technique. Due to the characteristics of asymmetric spinning, the roller feed should harmonize with the spindle rotation, and the roller path is derived through a discretization method. The thickness variation of oblique cone in different directions is coincident with the sine relation in axisymmetric shear spinning. The surface quality, especially the surface smoothness (the distribution of arrises) and surface roughness of the spun part, is discussed by analyzing the roller motion and important spinning parameters, and a smaller axial feed rate f and a smaller angle increment α can improve the surface quality.
The vehicle routing problem with time windows is a combinatorial optimisation problem in distribution logistics. It has been infrequently measured as a multi-objective optimisation problem for the benefit of customers. For the purposes of this research, the measurement of multi-objective vehicle routing problem with time windows will be in terms of a minimisation of the total distance travelled by all vehicles, the total number of vehicles used (management beneficial objectives) and the total gap between ready time and issuing time (customer beneficial objective). It is possible to satisfy customers by issuing the goods as close as possible to the customer ready time. This is because possibilities for going out of stock during the above said time gap (by chance of improper inventory maintenance) are reduced with a minimised total time gap, which in turn increases the sales orders for the manufacturing management. An improved genetic algorithm, called the fitness aggregated genetic algorithm, has been implemented to resolve the problem. The proposed algorithm incorporates a fitness aggregation approach and dedicated operators, such as selection based on aggregate fitness value and best cost route crossover, to resolve the multi-objective problem. The algorithm was validated on Solomon’s bi-objective benchmark models for the minimisation of the total distance travelled and total number of vehicles used, and the results formed by proposed algorithm are competitive to best known results. After validating the proposed algorithm on bi-objective models, the third objective – namely, the total time gap between ready time and issuing time – is included in the bi-objective model. The results show that the suggested algorithm creates improved customer-satisfied routes without drastically affecting the total distance travelled and total number of vehicles used.
On-line detection and measurements of tool wear is important to assure manufacturing accuracy, enhance manufacturing efficiency, and reduce manufacturing costs. In this research, adaptive neuro-fuzzy inference systems are utilized in conjunction with features extracted from three-axis cutting force data for the on-line detection and measurements of tool wear for precision boring of titanium components. Cutting force data were measured for carbide tools during the boring of titanium parts. At the end of every boring process, the average flank wear width was measured to determine the cutting tool conditions. Measurements were accomplished with the aid of a toolmaker’s microscope. In total, 14 features were obtained from the cutting force data. Euclidean distance measure was utilized to determine which features showed the best indication of cutting tool conditions. This approach can reduce the number of features for on-line detection and measurements of tool wear for precision boring of titanium parts. The selected two most prominent features were kurtosis of longitudinal force and average of the ratio between tangential force and radial force. On-line detection of boring tool wear obtained excellent results, using a 2x2 adaptive neuro-fuzzy inference systems, of being able to predict tool conditions on-line with 100% reliability. On-line measurements of boring tool wear also produced exceedingly successful results with a minimum error for a 1x10 adaptive neuro-fuzzy inference systems of 0.87%.
In the current global economy, organizations encounter problems related to resource constraints, and thus, systematic approaches for better resource utilization are a necessity. These systematic approaches investigate different resources in the organizations and attempt to specify which resources have higher importance for each business process and to what extent heterogeneous resources are utilized efficiently in the related business processes. This study presents an approach used to detect and analyze patterns of resource utilization. In this approach, the business processes and the related resources were initially identified and classified. Next, a questionnaire was designed to gather the required data for the importance and efficiency indicators. Afterward, classification methods were applied to determine which resource utilization opportunities (which specifications) correspond to different efficiency indicators and levels of importance. The results of the study reveal interesting patterns that can aid managers in obtaining deep insight into resource utilization in business processes. To demonstrate the applicability and usefulness of the proposed approach, the approach is applied to a case study of an automotive supplier.
Determination of accurate limit of cutting condition in order to obtain broken chips for various chip breaker geometries is essential to improve the machinability. This work presents a hybrid model based on the ratio of broken chip radius to the initial radius of chip to predict the type of chip regarding the characteristics of a chip breaker geometry and cutting parameters. An analytical geometrical model was developed to calculate the initial radius of chip. After running experimental tests for four types of chip breaker geometries and calculation of their chip ratio, type of chips and tool–chip contact were selected as two criteria for classifying chip ratio into three limits representing usable, acceptable, and unacceptable chips. Finally, the normalized data were used to train a neural network model to predict the type of chip which was verified by experiments carried out on a new chip breaker geometry. The trained network could predict the type of chip accurately by providing the geometrical details of the chip breaker and cutting parameters for the network.
This article presents a multi-objective formulation of a tolerance allocation model for interchangeable assembly of pin and hole to complement the need of small-scale industries where there exists two categories of machines, one for pin production and other for hole production. The two objectives considered in this article are minimum total cost of assembly and minimum clearance variation. The problem is formally defined as the determination of optimal Pareto set of tolerances for pin and hole for minimum total cost and minimum clearance variation of a hole and pin assembly, given the design clearance, the process capability of the machines defined with their standard deviations and the mean diameter of either pin or hole. An iterative search algorithm is proposed to explore the entire decision space and evaluate and obtain the Pareto optimal front. This article also presents how the optimal Pareto front of the model can be utilized by the manufacturer to set the optimal tolerances according to demands of the customers. Besides, the effect of process capabilities of pin and hole manufacturing machines on the optimality is discussed to understand their criticality in decision-making.
This article evaluates the finishing performance of ultrasonic-assisted double-disk magnetic abrasive finishing process on two paramagnetic materials (copper alloy and stainless steel) with different mechanical properties such as flow stress, hardness, shear modulus, and so on. The finishing experiments were performed based on response surface methodology. The results obtained after finishing have been analyzed to determine the effect of different process parameters such as working gap, rotational speed, and pulse-on time of ultrasonic vibration for both work materials and to study various interaction effects that may significantly affect the finishing performance by the process. The outcome of analysis for the two different work materials has been critically compared to understand the effect of the considered process parameters on the finishing performance of the process based on mechanical properties of the workpiece such as hardness. Furthermore, the scanning electron microscopy and atomic force microscopy were carried on the workpiece surface to understand the possible mechanism of material removal and the surface morphology produced after the finishing process.
Reconfigurable manufacturing systems focus on part family products with its customized flexibility. The characteristics of reconfigurable manufacturing systems help in rapid change of system and cost-effective manufacturing of products. Reconfigurable manufacturing systems can be modified both physically by changing layout, machines and material handling devices and logically by changing route, schedule, planning and so on, which is easy for implementation in reconfigurable manufacturing systems compare to other manufacturing systems. This article aims at configuration selection of a single-product flow-line reconfigurable manufacturing systems using ant colony optimization approach consisting of two phases. In the first phase, priority-based encoding technique is used to find feasible operation clusters, and the second phase uses ant colony optimization technique for minimizing the capital cost of the reconfigurable manufacturing systems. A case study is illustrated with the proposed approach by developing a tool box in MATLAB software. The approach is validated by finding 10-best configurations with the consideration of minimum capital cost. The results are also supported by convergence curve derived by the software.
Undesirable vibrations that occurred in cold rolling mills, widely known as chatter, are studied in this article by considering the interaction of three types of vibrations, namely, the longitudinal vibration of the rolled strip and the torsional and vertical vibrations of the upper work roll. The dynamic component of rolling force is determined using the quasi-static model under the assumption that the changes in roll gap and strip tension produce the variation of rolling force. The coupled vibrations of the work roll and rolled strip are mathematically governed by a set of 3-degree-of-freedom non-linear equations. Under chatter conditions, a new variable is introduced to represent the motion of the quasi-neutral point. A stability criterion for the motion of the quasi-neutral point is developed by studying the eigenvalues of the corresponding characteristic equation of the linearized parts of the non-linear equations. The chatter stability can then be examined by evaluating the determinants of five matrices. Numerical examples are given to show the stable and unstable vibrations in the cold rolling process. The unstable vibration would lead to skidding phenomenon and even break the rolled strip. The results presented in this article provide new insights into the dynamic interaction of the coupled vibrations and the dynamics of the rolling process.
In order to continuously improve the component roundness and productivity, an innovative investigation on through-feed centreless grinding is required particularly towards the 0.1–0.3 µm roundness accuracy of the components in the industrial production scale. In this process, the characteristics of the supporting and driving mechanism for the workpiece make the analysis of workpiece surface generation more complex than other grinding processes. This article presents an innovative approach for investigating the workpiece roundness generation in through-feed centreless grinding. Using homogeneous transformations, the geometries and the movements of the workpiece and the wheels are presented through a three-dimensional simulation model developed by the authors. This model and the associated simulations can be applied to investigate the workpiece kinematics and its rounding process under various geometric configurations and grinding parameters, and to further analyse the influences of these parameters on the workpiece roundness generation.
Abrasive flow machining is a pragmatic machining process used for part finishing. This article primarily focuses on the study of machining mechanism of high viscoelastic abrasive flow machining, with the aim to understand the relation among the abrasive media’s flow pressure, the material removal rate and the machining quality. The theoretical calculation models of the normal pressure on the inner surface of a circular tube and the wall sliding velocity are established based on rheology theory. The material removal rate of abrasive flow machining with a high viscoelastic abrasive media is derived. Numerical simulations with various machining conditions were conducted using the mathematical models proposed in this research and the obtained findings are discussed. The feasibility of these models introduced for high viscoelastic abrasive machining is also investigated and verified through actual experimental tests.
An experimental comparison of cutting fluid delivery nozzles was carried out with application to profile creepfeed grinding. A novel method of nozzle design and development involving rapid-prototyping enabled an exhaustive experimental approach. Circular, rectangular, and elliptical orifice nozzles were compared in terms of workpiece profile error, workpiece surface roughness, and grinding power over a variety of workpiece feedrates and cutting fluid jet pressures. For the grinding conditions used in this research, it was observed that, although the circular nozzle performed best, higher nozzle inlet pressures yielded smoother workpiece surface finishes.
Efficient construction in three-dimensional working procedure model has an important effect on the efficiency and quality of machining process planning. This article proposes an algorithm to mapping machining features to manufacturing feature volumes from B-rep of mechanical part, and then, the working procedure models are generated. The mapping strategy is performed in three steps. In the first step, three types of machining features, such as depression feature, protrusion feature and transition feature, are introduced. In the second step, the edges of the chosen seed face and its neighboring faces are searched in order to generate the machining feature faces. The last step applies a closure to the machining feature faces to generate a compact solid by applying additional neighboring faces and their extensions. Then, the working procedure models are formed by combining the mapped manufacturing feature volumes with the final parts model. Compared with the existing working procedure model’s generation methods, this approach can avoid the unnecessary conversions from the engineering drawing to three-dimensional process models and from the machining knowledge to the modeling knowledge, which can greatly reduce the planning time on modeling. To validate the feasibility and validity of this approach, two machined parts with complex machining features are tested in the developed prototype computer-aided process planning system.
Increasing global competition has forced many manufacturing enterprises (outsourcers) to focus on their core competences and outsource low value-added parts machining activities to suppliers to increase product quality and productivity as well as cut cost. While outsourcers or suppliers coordinate their decisions with partners for parts machining outsourcing, the present problem is how to timely achieve the most beneficial portfolio with the goal of gaining mutual benefit in a game structure. Based on the investigation conducted in Weinan National High-New Technology Zone of China, this article identifies several typical outsourcer–supplier Stackelberg game models for the order coordination of parts machining outsourcing and investigates one scenario of them in detail. Then, to solve the established bi-level programming model corresponding to the Stackelberg game, a solution procedure based on modified imperialist competitive algorithm is proposed. Finally, a case from a printing machinery enterprise is analyzed to validate the proposed model. This research is expected to improve the quality and effectiveness of coordination decision-making in parts machining outsourcing.
Process trimming (also can be called as trimming for process) helps to trim and eliminate process operations by redistributing their functions among other operations. It offers one way to eliminate key disadvantages in product and manufacturing process that other methods do not see. However, few methods have been disclosed in a structured way for process trimming effectively. Therefore, this article proposes an integrated process focused on technological process and product innovation to solve the key problems with process trimming-based TRIZ (theory of inventive problem-solving) approach. This method helps to identify and inventively solve the key problems and maximize use resource of system and supersystem. First, process trimming candidates are identified based on component function model, component trimming rules, process function model analysis, component–process interaction matrix, and root cause analysis. Then, three types of process trimming strategies are presented. Algorithm of process trimming is developed to identify key problems in technological process. TRIZ problem-solving tools are used to solve these key problems. Finally, a case study of refrigerator door foam innovative design and manufacturing process is investigated to test the efficiency of the approach. The innovative solution significantly decreases manufacturing defects and service cost.
Electrochemical honing is a hybrid finishing process combining advantages and simultaneously overcoming the individual limitations of electrochemical machining and mechanical honing. Finishing of conical gears by electrochemical honing is very complicated due their complex geometry. This article reports on the development of an innovative experimental setup and investigations on improving surface finish of straight bevel gears by electrochemical honing and its process productivity. A novel idea of using twin-complementary cathode gears was envisaged to ensure simultaneous fine finishing of all the teeth of straight bevel gear made of 20MnCr5 alloy steel. Effects of five important electrochemical honing parameters, namely, concentration, temperature and flow rate of electrolyte, rotary speed of workpiece gear, voltage on surface finish and material removal rate of the bevel gear were investigated. Improvement in the microstructure of electrochemical honing finished gear was studied using scanning electron microscopic images. To prove importance of hybridization in improving finishing capabilities of electrochemical honing, a comparative study of surface quality of a bevel gear finished by mechanical honing, electrochemical machining and electrochemical honing was done. The results revealed considerable improvements in the surface quality of the bevel gears finished by electrochemical honing. Electrolyte concentration of 7.5%, temperature of 32 °C, flow rate of 30 L/min, 8 V as voltage and speed of 40 r/min of the workpiece gear yielded the best combination of percentage improvements in average surface roughness (i.e. 58.5%), maximum surface roughness (i.e. 44.4%) and volumetric material removal rate (0.21 mm3/s). This work helps to establish electrochemical honing as a viable alternative bevel gear finishing process which has potential to overcome the limitations of conventional bevel gear finishing processes.
Optimizing flexible routing in flexible manufacturing systems ameliorates the efficiency of flexible manufacturing systems. In the present competitive market, accuracy in the planning stage plays an important role. Therefore, in this article, a production simulator system based on genetic algorithms is utilized to find the near-optimal flexible routing for flexible manufacturing systems. A combination of production simulator system and genetic algorithms is introduced to find the appropriate order of a set of operations for jobs that need to be operated on available machine tools in flexible manufacturing systems. In order to augment genetic algorithms, a matrix encoding method is incorporated. The proposed simulation is applied to numerical case studies of flexible routing for flexible manufacturing systems problem. The purpose of case studies is to demonstrate the successful applicability of the proposed method for flexible routing for flexible manufacturing systems problem.
A new slicing algorithm that uses multiple sets of cutting planes to automatically determine parting curves for three-dimensional parts is proposed. In this algorithm, one set of cutting planes is used to generate the slicing profiles, and two others are used to determine the intersection points with the inner and outer loops of the parting curves. The algorithm provides a highly effective solution for handling complicated models that contain free-form surfaces. The features of the algorithm are highlighted in three case studies using tessellated geometry in STL file format as the input. The resultant parting curves overcome many problems inherent in the current methods and can be used by various downstream computer-aided design systems for three-dimensional mold design.
The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.
A weak-rigid monolithic component is subjected to significant distortion after the removal of material. This condition is principally due to flexibility of the part and the release of initial residual stresses resulting from fabrication. This article reports a systematic study on the measurement of initial residual stresses and the distortion of a windshield frame part induced by material removal from the forged blanks of aluminum alloy 7085-T7452. A layer-removal method was employed to measure the stress profiles of the blank. The stresses after analytical correction were found to be closer to actual condition. The effect of material removal on distortion from stressed blank was investigated using the finite element analysis software ANSYS. The simulated results indicate that after the proportion of removed material exceeds 60%, part distortion becomes stable. The comparisons of the simulation with experimental data suggest sufficient agreement with conclusion that the use of finite element analysis proves to be an attractive and reliable method for predicting stress-induced distortion.
Cusps and scallops of hardened steel moulds produced by high-speed milling using a ball-nose end mill were mathematically modelled, characterised by microscopy and experimentally validated. The experimental results show that the part material is crushed or ploughed near the cutter centre, where the cutting speed is very low. This kinematic singularity, associated with tool feed, compresses and bends the ball-nose end mill axially. Because of this double effect, the end mill marks on the part at the end of the milling path cause surface damage and dimensional errors to the hardened mould. A mathematical model may predict the formation of the cusps and scallops and be of use in computer numerical control or computer-aided manufacturing programming to obtain the desired part topography.
Surfactant and graphite powder–assisted electrical discharge machining was proposed and experiments were performed on titanium alloy in this investigation. Analysis was carried out to observe changes in dielectric fluid behaviour, material removal rate, surface roughness, recast layer thickness, surface topography and energy-dispersive X-ray spectroscopy. It was found out that the addition of surfactant to dielectric fluid (electrical discharge machining oil + graphite powder) improved the material removal rate and surface roughness. It was noticed to have reduced the recast layer thickness and agglomeration of graphite and sediment particles. Biface material migrations between the electrode and the workpiece surface were identified, and migration behaviour was powerfully inhibited by the mixing of surfactant. Surfactant added into dielectric fluid played an important role in the discharge gap, which increased the conductivity, and suspended debris particles in dielectric fluid reduced the abnormal discharge conditions of the machine and improved the overall machining efficiency.
Manufacturing systems are constrained by one or more bottlenecks. Reducing bottlenecks improves the entire system. Finding bottlenecks, however, is a difficult task. In this study, a new bottleneck detection method based on theory of constrains and sensitivity analysis is presented to overcome the disadvantages of existing bottleneck identification methods for a job shop. First, a bottleneck index matrix is obtained by examining the sensitivity of system production performance to the capacity of each machine. Technique for order preference by similarity to ideal solution is then employed to calculate the comprehensive bottleneck index of each machine. Based on the calculation result, bottleneck machine clusters under different hierarchies are obtained through hierarchical cluster analysis. The designed identification approach, as a prior-to-run method, can identify bottleneck machine clusters under different hierarchies before the overall system circulation, thereby providing good guidance for subsequent production optimization. Finally, a set of job-shop scheduling problem benchmarks with different scales is selected for comparison between the proposed approach and existing approaches, such as, the shifting bottleneck detection method, the bottleneck detection method based on orthogonal experiment, and the bottleneck cluster identification method. By comparison, the proposed approach is proven to be credible and superior.
In recent years, various reasons for improvement of performance and efficiency in ultrasonic vibration–assisted machining processes have been reported, which were mostly descriptive and without sufficient analytical and empirical proofs. Among the different machining processes, the least amount of experimental data and analytical relations exist about ultrasonic-assisted milling. In this article, for the first time in ultrasonic-assisted milling, we have determined the times of tool–workpiece engagement and their separation from each other in each vibration cycle and then investigated the influence of vibration amplitude and cutting speed on tool–workpiece effective engagement in ultrasonic-assisted milling. Contrary to ultrasonic-assisted turning, cutting time in each vibration cycle in ultrasonic-assisted milling is different from each other. With the aid of comprehensive experiments at tool–workpiece engagement angles smaller than 90°, we have proved that the main reason for average cutting force decrease in ultrasonic-assisted milling compared with conventional milling is the separation of tool and workpiece that occurs in a portion of each vibration cycle, and other factors such as change of friction behavior have less importance. At investigated tool–workpiece engagement angles, experimental and analytical results agree with each other.
Cutting force coefficients were conventionally described as the power function of instantaneous uncut chip thickness. However, it was found that the changes in the three controllable machining parameters (cutting speed, feed and axial cutting depth) could significantly affect the values of cutting coefficients. An improved cutting force model was developed in this article based on the experimental investigation of end milling titanium alloy (Ti6Al4V) with polycrystalline diamond tools. The relationships between machining parameters and cutting force are established based on the introduction of the new cutting coefficients. By integrating the effects of varying cutting parameters in the prediction model, cutting forces and the fluctuation of cutting force in each milling cycle were calculated. Validation experiments show that the predicted peak values of cutting forces highly match the experimental results; the accuracy of the model is up to 90% in predicting instantaneous cutting forces.
Machining of metal matrix composites has always been challenges for manufacturing engineers due to the presence of hard and brittle reinforced particles. In this article, a new way of alternate application of electrical discharge grinding and abrasive grinding has been applied through the use of slotted grinding wheel. The developed machining process has been named as slotted electrical discharge abrasive grinding. The performances of slotted electrical discharge abrasive grinding process are tested on aluminum–silicon carbide–graphite (Al/SiC/Gr) metal matrix composite workpiece. The experiments were performed using one parameter at a time approach considering the effect of current, pulse on-time, pulse off-time, wheel speed and grit number on material removal rate and average surface roughness. It has been found that current ranges from 3 to 15 A and wheel speed ranges from 700 to 1300 r/min are more appropriate for machining of Al/SiC/Gr composite material within the ranges of selected parameters.
Error compensation technology as an economical and effective method for improving the machining accuracy of the machine tools has been widely applied in the manufacturing. How to quickly and accurately obtain machine tool error is an important prerequisite for achieving the above task. A laser tracker is adopted the multi-station and time-sharing measurement principle to achieve quick and accurate identification of the geometric errors of the machine tool. In this article, the error of single-station measurement of laser tracker is analyzed first, and then the principle and algorithm of multi-station and time-sharing measurement are given. Based on the kinematic model of the machine tool, the mapping relation equations between the space motion error and individual geometric error of the machine tool are established, and two different identification algorithms are derived, respectively. Meanwhile, the identification accuracy of two algorithms and the impact of different measurement areas and squareness errors on two algorithms are compared and analyzed in depth. The experiment results indicate that higher identification accuracy can be obtained by the second algorithm, and individual geometric error of the machine tool can be quickly and accurately separated by this algorithm.
The mechanism of incremental sheet metal forming is based on plastic and localized deformation of sheet metal. The sheet metal is formed using a hemispherical-head tool in accordance with the path programmed into the computer numerical control milling machine controller. Experimental and numerical analyses have been performed previously on the application of ultrasonic vibration to various metal forming processes. However, thus far, the effects of ultrasonic vibration on incremental sheet metal forming have not been investigated. This article presents the process of design, analysis, manufacture and testing of a vibrating forming tool for the development of ultrasonic vibration–assisted incremental sheet metal forming. The results obtained from modal analysis and natural frequency measurement of the vibrating tool confirmed the emergence of a longitudinal vibration mode and resonance phenomenon in the forming tool. Then, the effect of ultrasonic vibration on incremental sheet metal forming was studied. The obtained experimental results from the straight groove test on Al 1050-O sheet metals showed that ultrasonic vibration led to decrease in the following parameters as compared with conventional incremental sheet metal forming: applied force on forming tool axis, spring-back and surface roughness of formed sample.
In this article, an advanced analytical formulation is developed to predict thickness change of an aluminum/copper clad sheet. Springback analytical formulation is also introduced using the combination of advanced and primary bending theories in air bending process. Experiments were performed to verify analytical results and to investigate the effect of different geometrical parameters such as punch stroke, die opening, punch radius and setting condition on the springback. It was observed that die opening had the most striking effect, while setting condition had a negligible effect on springback. On the other hand, setting condition played a crucial role on thickness change in bent clad sheets. Clad sheet thickened in the Al/Cu setting condition, while in the Cu/Al setting it thinned. Finite element method simulation was also applied to verify analytical predictions of the thickness change and study stress distribution in the layers of the clad sheet. Good correlation was observed between analytical and numerical results.
Elastic connection of spindle–tool holder is one of the weak points of spindle systems. It directly affects dynamic characteristics of machining system. Stiffness modeling of spindle–tool holder is the key problem in dynamic analysis of spindle system. Considering the influence of cutting force, an analytical method combining classic elasticity theory with fractal theory is proposed to estimate the contact stiffness at the spindle–tool holder interface. The effectiveness of the proposed method is validated by self-designed experiment. An approximate model is proposed to replace finite element model in the processing of identification of contact stiffness of spindle–tool holder in order to save calculation time. On that basis, effects of cutting force on contact stiffness of spindle–tool holder are investigated in this article. The conclusion can be drawn that cutting force has great effect on stiffness of spindle–tool holder. Contact stiffness of spindle–tool holder can be obtained by the method proposed in this research on the premise of not making prototypes or utilizing hammer-hitting pulse-inspirit method. The calculating model and method in this article can be implemented to solve the contact stiffness at the spindle–tool holder during the design stage.
In micro-electro-discharge machining drilling, the problem of tool wear is a well-known fact. In order to minimize the effect of tool wear on the accuracy of fabricated product, an online tool wear monitoring and compensation system needs to be integrated with the micro-electro-discharge machining machine. The existing monitoring and compensation system very much relies on the pulse discrimination. The available systems assume that pulses are isoenergetic and are applicable to a single parametric setting only. In order to make the system more robust, a new pulse discrimination and tool wear compensation strategy which is suitable for a wide range of parametric settings is proposed. In this context, an empirical relationship between "average energy" (AE) and "volume removal per discharge" (VRD) is established and verified with experimental results.
In this article, quality analysis of the assembled phase-only liquid crystal on silicon devices is presented based on experiences using the flexibility and scalability of die-level assembly process. The research contents mainly consist of quality control and optimisation of liquid crystal filling process and device overall quality assessment including the thickness uniformity of liquid crystal layer with post-assembly inspection. To summarise, pre-production prototype phase-only liquid crystal on silicon devices with high quality has been developed in high reproducibility using a die-level assembly process, the robust glue deposition is performed, liquid crystal filling process in isotropic phase is presented and thickness variation can be controlled in the range of /4.
Distortion mitigation techniques for large parts constructed by additive manufacturing processes are investigated. Unwanted distortion accumulated during deposition is a common problem encountered in additive manufacturing processes. The proposed strategies include depositing equal material on each side of a substrate to balance the bending moment about the neutral axis of the workpiece and applying heat to straighten the substrate. Simple finite element models are used to predict the effectiveness of the mitigation strategies in order to reduce computation time and to avoid costly experiments. The strategy of adding sacrificial material is shown to be most effective and is then applied to the manufacture of a large electron beam deposited part consisting of several thousand deposition passes. The deposition strategy is shown to reduce the maximum longitudinal bending distortion in the large additive manufacturing part by 91%. It is shown that after the distortion mode of concern is identified, simple finite element models can be used to study distortion accumulation trends relevant to the large part. Experimental observations made here, as well as finite element model results, suggest that the order in which the balancing material is added significantly affects the success of the proposed distortion mitigation strategy.
AC-170PX (AA6014) alloys are typically used in lightweight automobile vehicles. Laser welding can be a viable tool for the assembly of components. However, porosity is often generated during aluminium welding. In this article, an investigation is reported on the characteristics of porosity formation in high-power disc laser welding of AC-170PX aluminium alloy sheets in two weld joint configurations: fillet edge and flange couch with three different filler wires of 4xxx, 3xxx and 5xxx aluminium series for each joint. Porosity, microstructures, tensile strengths and joint geometry were investigated. It has been found that the use of filler wires with higher Mg and Mn content such as AA5083 and AA3004 leads to a significant reduction in porosity to less than 1.5% in both types of joints compared with up to 80% porosity with the silicon-rich AA4043 wire. The mechanism that led to this improvement is discussed.
This article presents a methodology that provides a continuous assessment of predictive maintenance (PdM) technologies with respect to specific business scenarios. The methodology integrates existing reliability and maintenance business analysis techniques and standards. The positive impacts that may have implementing these technologies have always been in mind. A critical simulation step is also added where different predictive maintenance strategies are simulated in order to obtain the optimal maintenance strategy. This Monte Carlo simulation relies on the reliability information based on the probability density distribution of failure for the system or component, providing as a result the optimal strategy among the proposed options. The article finally explains how this methodology has a positive impact not only on the cost-effectiveness of maintenance processes, but also on the maintenance information available.
Laser cladding by cold-wire feeding is known as an efficient cladding method due to its advantages, such as near 100% material utilization, high deposition rate, and flexible adaptation to the cladding position. However, it has very stringent requirements on the operative conditions, such as a small range of wire feeding rate and precise wire feeding position. The aim of this work was to investigate the laser hot-wire cladding technique, which improved the productivity and stability of the process significantly with respect to laser cold-wire cladding. The external preheating of the filler wire resulted in reduction in required laser power, a low dilution, and a higher deposition rate. A comparison was made between laser cold-wire cladding and laser hot-wire cladding of Inconel 625 on mild steel, with respect to the clad characteristics, microstructure, and hardness. An optimization of the main processing parameters in laser hot-wire cladding, such as the laser power, laser spot size, laser scanning speed, wire feeding orientation and position, wire preheating voltage, and wire feeding rate, was performed. The optimal parameters were used to create a multi-track deposit.
This article integrates the company operations decisions (i.e. location, production, inventory, distribution, and transportation) and finance decisions (i.e. cash, accounts payable and receivable, debt, securities, payment delays, and discounts) in which the demands and return rate are uncertain, defined by a set of scenarios. The cash flow and budgeting model will be coupled with supply chain network design using a mixed integer linear programming formulation. The article evaluates two financial criteria, that is, the change in equity and the profit as objective functions. The results indicate that objective functions are partially interdependent, that is, they conflict in certain parts. This fact illustrates the inadequacy of treating process operations and finances in isolated environments and pursuing objective myopic performance indicators such as profit or cost. Due to the importance of the supply chain network design problem, a multi-objective robust optimization with the max–min version is extended to cope with the uncertainty. A solution approach integrating Benders’ decomposition method with the scenario relaxation algorithm is also proposed in this research. The improved algorithm has been applied to solve a number of numerical experiments. All results illustrate significant improvement in computation time of the improved algorithm over existing approaches. For a problem, the proposed algorithm shows a significant reduction in computational time compared with the Benders’ decomposition and scenario relaxation that shows the efficiency of the proposed solution method.
With the currently strict environmental law in present days, researchers and industries are seeking to reduce the amount of cutting fluid used in machining. Minimum quantity lubrication is a potential alternative to reduce environmental impacts and overall process costs. This technique can substantially reduce cutting fluids in grinding, as well as provide better performance in relation to conventional cutting fluid application (abundant fluid flow). The present work aims to test the viability of minimum quantity lubrication (with and without water) in grinding of advanced ceramics, when compared to conventional method (abundant fluid flow). Measured output variables were grinding power, surface roughness, roundness errors and wheel wear, as well as scanning electron micrographs. The results show that minimum quantity lubrication with water (1:1) was superior to conventional lubrication-cooling in terms of surface quality, also reducing wheel wear, when compared to the other methods tested.
The coexistence of high levels of strength and toughness is necessary for the microalloyed steels used in natural gas pipelines. The welding thermal cycle can significantly change the microstructures and therefore the mechanical properties of the girth welded pipelines. Thus, the experimental investigation on the welded material properties is required for assessing the structural integrity of the pipelines. In this article, the metallurgical characteristics of the multi-pass girth welds on API X70 steel pipes with 56 in outside diameter and 0.780 in wall thickness were determined for the first time using chemical analysis and standard metallography. The chemical analysis showed different chemical compositions in different weld passes. The amount of carbon in the weldment increased in comparison with the base metal, although the microalloy elements in the weld gap decreased by increasing the pass number. The metallographic investigation by optical microscope demonstrated the different microstructures in different sub-zones of the welded joint. The images obtained from scanning electron microscope also presented the dendritic and acicular structures in the root and cap passes, respectively. The observed hard phases in the weldment, such as martensite, had direct effects on the mechanical properties of the weldment and heat-affected zone.
Waste Electrical and Electronic Equipment is one of the major waste streams in terms of quantity and toxicity, and a critical step in Waste Electrical and Electronic Equipment end-of-life processing is through disassembly. Compared with full disassembly, which is a sub-optimal solution due to its high operational cost, selective disassembly is more economic and practical as only selected parts with recycling potential are considered. In this article, a systematic selective disassembly approach for handling Waste Electrical and Electronic Equipment with a maximum disassembly profit in accordance to the Waste Electrical and Electronic Equipment and Restriction of Hazardous Substances Directives has been developed. First, a space interference matrix is generated based on the interference relationship between individual components in the three-dimensional computer-aided design model of Waste Electrical and Electronic Equipment. A matrix analysis algorithm is then applied to obtain all the feasible disassembly sequences through the obtained space interference matrix in a three-dimensional environment. Second, an evaluation and decision-making method is developed to find out an optimal selective disassembly sequence from the obtained feasible disassembly sequences. The evaluation takes into account the disassembly profit and requirements of the Waste Electrical and Electronic Equipment and Restriction of Hazardous Substances Directives, which regulate on recycling rates of different types of products and removal requirements of (1) hazardous, (2) heavy and (3) high-value components. Thus, an optimal solution is a selective disassembly sequence that can achieve the maximum disassembly profit, while complying with the Waste Electrical and Electronic Equipment and Restriction of Hazardous Substances restrictions based on a brute-force search method. Finally, an industrial case on Changhong liquid crystal display televisions of the type LC24F4 is used to demonstrate the effectiveness of the developed approach.
NiTi is a shape memory alloy, mostly employed in cardiovascular stents, orthopedic implants, orthodontic wires, micro-electromechanical systems and so on. The effective and net shape machining of NiTi is very critical for excellent response of this material in medical and other applications. The present experimental work on wire electrical discharge machining process identifies the influence of process parameters that affect the cutting rate, dimensional shift and surface roughness while machining of porous nickel–titanium (Ni40Ti60) alloy. Porous Ni40Ti60 alloy was produced in-house using powder metallurgy technique. Response surface methodology–based central composite rotatable design has been used for the planning of experiments on wire electrical discharge machining. Empirical relations have been developed between the process parameters (pulse on-time, pulse off-time, servo voltage and peak current) and response variables. Desirability approach has been used for optimizing the three response variables simultaneously. Confirmation experiments were also performed at the optimized settings and reflect a close agreement between the predicted and experimental values (percentage error varies from –6.13% to +6.85%). Using wire electrical discharge machining, NiTi alloy can be machined easily and successfully in single-cutting operation, but after the first cut in wire electrical discharge machining, a surface projection appears on work surface which is the unmachined material on work surface.
In this work, a computational approach is proposed in order to help establish the effect of various flow-drilling screw process and material parameters on the quality and the mechanical performance of the resulting flow-drilling screw joints. Toward that end, a sequence of three distinct computational analyses is developed. These analyses include the following: (a) finite element modeling and simulations of the flow-drilling screw process; (b) determination of the mechanical properties of the resulting flow-drilling screw joints through the use of three-dimensional, continuum finite element–based numerical simulations of various mechanical tests performed on the flow-drilling screw joints and (c) determination, parameterization and validation of the constitutive relations for the simplified flow-drilling screw connectors, using the results obtained in (b) and the available experimental results. The availability of such connectors is mandatory in large-scale computational analyses of whole-vehicle crash or even in simulations of vehicle component manufacturing, for example, car-body electro-coat paint-baking process. In such simulations, explicit three-dimensional representation of all flow-drilling screw joints is associated with a prohibitive computational cost. The approach developed in this work can be used, within an engineering-optimization procedure, to adjust the flow-drilling screw process and material parameters (design variables) in order to obtain a desired combination of the flow-drilling screw joint mechanical properties (objective function).
Tailor-welded blank is one of the promising technologies in the application of lightweight materials for auto body parts manufacturing. The material discontinuity across the weld line results in an inhomogeneous deformation and weld line displacement. In this study, a two-dimensional analytical model is proposed to predict the tension distribution along the cross section. An energy method is used to calculate the restraining force due to bending, sliding, and unbending phenomena on the die and punch radii. To control the weld line movement, a blank holder force control strategy is proposed to achieve force equilibrium at the bottom of the part across the weld line. Finite element simulations are performed to study the effect of die and punch radii, friction coefficient, thickness ratio, and blank holder forces on the weld line displacement in strip drawing process. Under a uniform blank holder force, the weld line moves toward the thicker/stronger side implying a higher blank holder force is required for the thinner/weaker side. The results show that the weld line displacement can be controlled by an appropriate blank holder force adjustment. In order to control the weld line movement in square cup deep drawing, blank holder force on the thinner side is increased and its influences on the deformation process are investigated. Comparisons of material draw-in, weld line movement, and forming force show a good agreement between the theoretical, numerical, and experimental results.
A new slip-line field model and its associated hodograph of rounded-edge cutting tool were developed for orthogonal micro-cutting operation using matrix technique. The new model considers the existence of dead metal zone in front of the rounded-edge cutting tool. The ploughing forces, chip up-curl radii, chip thicknesses, primary shear zone thicknesses and lengths of bottom side of the dead metal zone are obtained by solving the model depending on the experimental resultant force data. The effects of cutting edge radius, uncut chip thickness, cutting speed and rake angle on these outputs are specified.
Routing flexibility is a major contributor towards flexibility of a flexible job shop manufacturing system. This article focuses on a simulation-based experimental study on the effect of routing flexibility and sequencing rules on the performance of a stochastic flexible job shop manufacturing system with sequence-dependent setup times while considering dynamic arrival of job types. Six route flexibility levels and six sequencing rules are considered for detailed study. The performance of manufacturing system is evaluated in terms of flow time related and due date–related measures. Results reveal that routing flexibility and sequencing rules have significant impact on system performance, and the performance of a system can be increased by incorporating routing flexibility. Furthermore, the system performance starts deteriorating as the level of route flexibility is increased beyond a particular limit for a specified sequencing rule. The statistical analysis of the results indicates that when flexibility exists, earliest due date rule emerges as a best sequencing rule for maximum flow time, mean tardiness and maximum tardiness performance measures. Furthermore, smallest setup time rule is better than other sequencing rules for mean flow time and number of tardy jobs performance measures. Route flexibility level two provides best performance for all considered measures.
An analytical and finite element investigation of the effect of different cryogenic cooling nozzle configurations on temperature and residual stress in a model friction stir weld is presented. A new configuration adopting a distributed cooling approach is proposed based on an analytical cooling model. Finite element models are implemented to verify the effect of distributed cooling on welding temperature and longitudinal residual stress. The results presented indicate that new active cooling methods can improve mitigation of welding-induced residual stress.
The influence of shot-peening parameters on surface integrity of 7055 aluminum alloy is investigated based on shot-peening experiments. Surface integrity measurements, fatigue fracture analysis and fatigue life tests are conducted to reveal the effect of surface integrity on crack initiation and fatigue life. The results show that surface roughness increases significantly, and irregular pits and bumps appear on surface after shot-peening; grain on subsurface is refined and produces a shift and distortion in the pellets hit direction; compressive stress can be detected on all machined surfaces. Shot-peening parameters have significant impact on micro-hardness. In comparison with the milled specimen, fatigue life of peened specimens is improved by about 23.8, 3.96 and 1.01 times. Fatigue source zone transfers from stress concentration location on surface to subsurface due to the lower surface roughness and lager residual compressive stress.
Fluid jet polishing is an enabling ultra-precision machining technology, which has not only been widely used for removing machine tool marks in order to achieve super finished surfaces, but also for controlling the form accuracy in machining freeform surfaces. Due to the complex machining mechanism, it is difficult to model the material removal rate accurately with consideration of a lot of operational parameters in fluid jet polishing. In this article, the optimal operational parameters and the significance of the important parameters are determined by the Taguchi design of experiments. Hence, a computational fluid dynamics–based analysis is built for the determination of the material removal rate in fluid jet polishing. In this model, the impact information of the particles with respect to the workpiece is computed by computational fluid dynamics simulation which is then coupled with a local mechanics erosion model so as to predict the detailed distribution of the material removal rate in fluid jet polishing. To verify the computational fluid dynamics–based erosion model, a series of polishing experiments have been conducted. The experimental results are found to agree well with the predicted form error and the pattern of the material removal rate by the integrated erosion prediction model.
'-strengthened nickel-based superalloys are developed for high-performance systems such as jet engines, internal combustion engines, and gas turbines. Their excellent properties are given by specifically designed microstructure. Unfortunately, the structure is deformed during machining. Too much deformation generated results in components with low mechanical integrity and reduced in-service life. Experimental investigations indicated that the machining affected zone or subsurface damage formation for nickel-based superalloys is an atypical phenomenon; its dependence on the process parameters is fundamentally different from the conventional materials. This research investigates subsurface damage formation in orthogonal cutting tests performed on nickel-based superalloys, followed by empirical and numerical modeling. The simulations are used to estimate the depth of the subsurface damage and are compared with the experimental results. The knowledge can then be applied to select optimum cutting parameters for an acceptable depth of subsurface damage.
Little practical results are known about the cutting tool optimal replacement time, specifically for machining of composite materials. Due to the fact that tool failure represents about 20% of machine down-time, and due to the high cost of machining, in particular when the work piece’s material is very expensive, optimization of tool replacement time is thus fundamental. Finding the optimal replacement time has also positive impact on product quality in terms of dimensions and surface finish. In this article, two new contributions to research on tool replacement are introduced. First, tool replacement mathematical models are proposed. These models are used in order to find the optimal time to tool replacement when the tool is used under variable machining conditions, namely, the cutting speed and the feed rate. Proportional hazards models are used to find an optimal replacement function. Second, this model is obtained during turning titanium metal matrix composites. These composites are a new generation of materials which have proven to be viable in various industrial fields such as biomedical and aerospace, and they are very expensive. Experimental data are obtained and used in order to develop and to validate the proportional hazards models, which are then used to find the optimal replacement conditions.
The objective of this study is to model the temperature distributions in milling analytically. In this article, previous research on heat generation and heat dissipation in the machining process was reviewed and then the temperature model in intermittent cutting with continuously varying chip thickness was established. The experimental study to measure cutting temperature in milling Ti6Al4V utilizing semi-artificial thermocouple was presented. The predicted and experimental results for milling process were presented and compared. The results showed that the proposed mathematical model could predict cutting temperature with high accuracy.
The material removal process of micro electrical discharge machining is based on the instantaneous ultra-high temperature generated by a series of repetitive discharge pulses. Due to the size effects, the polycrystal cannot be considered as continuous and homogeneous material when machining is in micron scale, and the effects of material microstructure should not be neglected. In this article, the thermoelectric characteristics of grain and grain boundary are discussed, and the influence of grain size on the machining performances in micro electrical discharge machining is researched. Two kinds of austenitic stainless steels (AISI 304) which are different in grain size are chosen as the workpieces in experiments. It is verified by both theory models and experimental results that the smaller the grain size, the higher the material removal rate, under the same discharge conditions. Both thermal conductivity and melting point of the grain boundary are lower than those of the grain because of the grain boundary segregation. The effective thermal conductivity and local effective melting point of polycrystalline materials vary with their grain sizes since the grain boundary volume fractions change. As a consequence, the material removal rate of micro electrical discharge machining has direct relationship with grain size of the workpiece.
In this study, dissimilar joints of AA5083-H116 and AA7075-T6 aluminum alloys were successfully made by friction stir welding technique. The microstructure and mechanical behavior of the welded joints were investigated at different rotational and traverse speeds. A mathematical modeling was developed to demonstrate a relationship between the friction stir welding parameters and the ultimate tensile strength of the dissimilar joints. Then, the mathematical modeling was optimized by genetic algorithm in order to find the optimum condition in which the maximum tensile strength of welded joints can be achieved. Eventually, genetic algorithm results confirmed that the maximum tensile strength of welded joints is achievable in rotational and traverse speeds of 500 r/min and 50 mm/min, respectively. The maximum error between experimental data and predicted model was less than 1%.
In this article, a novel approach for assessment and ranking of maintenance process indicators as well as maintenance cost indicators and maintenance equipment indicators using the fuzzy sets approach and genetic algorithms is presented. Weight values of these indicators are defined using the experience of decision makers from analyzed small and medium enterprises (total number of 197 persons) and calculated using the fuzzy sets approach. In the second step, a model for ranking and optimization of maintenance performance indicators and small and medium enterprises by using genetic algorithm is presented. The presented approach enables multi-objective optimization of selected key performance indicators in the scope of optimization of maintenance performances. The value of optimization was tested on a group of small and medium enterprises which proved that improvement of maintenance performance could be more significant (or performed at the shorter period of time) if the specific key performance indicators were targeted for improvement. The presented solution could provide identification of strengths and weaknesses (comparing key performance indicators), learning from a leading organization (in prioritization of key performance indicator improvement) and improvement of maintenance performance.
Maintenance nowadays not only plays a crucial role in the usage phase, but is fast becoming the primary focus of the design stage—especially with general increased emphasis on product service. The modularization of maintenance has been explored rarely by previous researchers, despite its significant potential benefit. Existing modular design methods on life cycle do not sufficiently improve maintenance performance as a whole. In effort to remedy this, this article considers relevant maintenance issues at early stages of product development and presents a novel modular methodology based on the simultaneous consideration of maintenance and modularity characteristics. The proposed method first employs the design structure matrix to analyze the comprehensive correlation among components. Next, based on graph theory, initial modules with high cohesion and low coupling are generated. After that, a maintenance performance multi-objective model is established for further optimization to minimize maintenance costs, minimize differences in the maintenance cycle, and maximize system availability. To conclude, an improved strength Pareto evolutionary algorithm 2 is used for modular optimization. The complete methodology is demonstrated using a case study with a hydraulic press, where results reveal that the optimized modules can reduce maintenance cost under the premise of approximately constant modular performance.
This article discusses the effects of process parameters (feed and spindle speed) on quality characteristics (thrust force, torque, surface roughness and ovality) for standard and special geometric design of a drill body in dry drilling of pultruded and sheet moulding compound thick composites. Pultruded (non-laminated) and sheet moulding compound (laminated) thick glass fibre–reinforced plastic composites with a higher percentage of fibre weight fraction are extensively used in construction of bridges, prefabricated platforms, ballistic applications, structural applications, instrument bases and automotive load floors, and therefore, prediction of better performance drill helps the fabrication industry in making good quality holes. The drilling experiments using coated tungsten carbide drills, twist drill (standard geometry) and ratio drill (special geometry) of diameter of 10 mm were conducted using response surface methodology. Analysis of variance of the experimental results reveals that for both twist drill and ratio drill, feed is more significant in influencing the quality characteristics. The experimental values obtained for quality characteristics are empirically related to process parameters by developing response surface models using Design-Expert software. Analysis of the experimental results reveals that ratio drill performs better in pultruded composites and twist drill performs better in sheet moulding compound composites. The optimal process parameter levels within the selected range for minimizing all the quality characteristics together were determined.
This article presents a study of high-temperature heating of AISI 304L stainless steel to induce deformations in a manufactured part. Small square samples of AISI 304L were heated to deform a slot using an oxy-acetylene torch. The sample temperature profiles were measured using three thermocouples with maximum temperature values ranging from 760 °C to 1130 °C. Three-dimensional thermo-structural finite element models were created to predict the magnitude of permanent deformation and were validated experimentally. Torch modeling parameters were optimized numerically using a series of finite element simulations. The finite element predictions for deformation were found to be in reasonable agreement with the experimental results. The variation in yield strength of AISI 304L was shown to be an important factor in affecting the magnitude of deformations. Repeated heating experiments also demonstrated additive plastic strain with each heating cycle. The results provide a means to use high temperatures to purposefully alter the dimensions of a slot in a manufactured part but with varying accuracy.
This study focused on the optimization of micro-milling parameters for two extensively used aerospace materials (titanium and nickel-based superalloy). The experiments were planned using Taguchi experimental design method, and the influences of spindle speed, feed rate and depth of cut on machining outputs, namely, tool wear, surface roughness and cutting forces, were determined. Tool wear, surface roughness and cutting forces measured in micro-milling of Ti6Al4V titanium alloy and Inconel 718 workpiece materials were optimized by employing Taguchi’s signal-to-noise ratio. The percentage contribution of micro-milling parameters, namely, spindle speed, feed rate and depth of cut, on tool wear, surface roughness and cutting forces was indicated by analysis of variance. The regression models identifying the relationship between the input variables and the output responses were also fitted using experimental data to predict output responses without conducting the experiments. Efficiency of regression models was determined using correlation coefficients, and the predicted values were compared with experimental results. From results, it was concluded that the established regression models could be employed for predicting tool wear, surface roughness and cutting forces in micro-milling of Ti6Al4V titanium alloy and Inconel 718 workpiece materials.
In this article, a path planning algorithm for nonholonomic mobile flexible manipulators is presented that computes the robot trajectory by maximizing pose stability measures. Zero moment point criterion is used as a performance index for the system stability, which regards the mass moment of inertia of the mobile base. In dynamic analysis, an efficient model is employed to describe the treatment of flexible structure, in which both the geometric elastic nonlinearity and the foreshortening effects are considered. The optimization strategy is based on the indirect solution of the open-loop optimal control problem. Necessary optimality conditions in the form of Pontryagin’s minimum principle are established, which leads to a standard form of a two-point boundary value problem. A new objective function is proposed to improve stability for mobile flexible robot. In order to initially check the validity of the dynamic equations, the proposed model has been implemented and tested on a fixed-base flexible arm undergoing large deflection. A simulation study has been carried out to investigate further the validity and effectiveness of the mobile flexible manipulators on finding the optimal path between two points with stability consideration. The results clearly show the effect of flexibility and tip over stability on the mobile manipulators.
The real-time acquisition of machining task progress is one of the most important tasks of production management and is an essential aspect of manufacturing information. Targeted to the machining mode of mixed-category workpieces in job shops, a method for the acquisition of real-time machining task progress is proposed. The method is based on both the power feature of workpiece machining and the incremental learning Lagrangian support vector machine. First, the framework for this method is presented in a straightforward manner. Second, by analysing the characteristics of power change during the machining process, the power feature vector, which reflects the characteristics of workpiece machining, is designed for Lagrangian support vector machine. Then, based on the principle of incremental learning Lagrangian support vector machine, which can address the classification of mixed-category workpieces and the problem of an insufficient number of training samples for training the initial classifiers during the actual machining process, a detailed application of this method is constructed for workpiece classification and the acquisition of machining task progress. Finally, the effectiveness of this method is empirically tested by application to a case study.
This work is to assess whether car bumpers can be formed using single-stroke pressing instead of conventional double-stroke pressing. Some basic characteristics of the car bumper forming process are also clarified. An incremental elasto-plastic finite-element method is used to simulate a bumper forming process using high-strength steel and laminate sheets under the plane strain condition. Simulations clearly demonstrate the processes involved in single-stroke forming. A three-layer steel/polymer/steel laminate developed for vibration-damping in an automobile bumper is also tested to demonstrate how shear defects occur between the two skin steel layers along the entire length of the laminate sheet in simulation. The springback phenomenon resulting from the elastic recovery is observed in simulations of the final bumper shape. Accordingly, experiments for high-strength steel sheet were performed to verify the numerical simulation and to investigate how process geometry conditions affect the springback angle, which is an essential consideration when assessing and controlling the final bumper shape in practice. This work improves understanding of the bumper forming processes used in the automotive industry.
The importance of integration of process planning and scheduling is evident in today’s competitive manufacturing system. Meanwhile, the setup planning plays an important role for integration, because setup planning is done after process planning, just before scheduling. In this article, a new approach for setup planning for multiparts is introduced to realize integration of process planning and scheduling with more details of manufacturing constraints for setup planning. For this purpose, the necessary and unnecessary (preferred) constraints are defined for setup formation and a new matrix is presented to distinguish these and to specify the precedence of operations. The simulated annealing is used in setup planning for N parts simultaneously based on multi-technical and scheduling objectives. The proposed system is based on the machining operation instead of features, to select machine tools more accurately. Another factor for the selection of machine tools is tolerances that are considered in this article and greatly affected the machining cost. An illustrative example is presented to show the effectiveness of the operation-based system and the second example is presented to demonstrate the influence of multipart setup planning versus single-part setup planning. The results show that considering multiparts improves the scheduling objectives such as makespan.
Laser micro-machining is a promising manufacturing solution for fabricating complex micro-engineering products in wide range of materials that incorporate different multi-scale functional features. Optical beam deflector systems are key components in laser micro-machining systems, and they are one of the main factors determining the processing speed and hence machining throughput. However, their performance is speed dependent and the negative dynamics effects have a direct impact on the laser micro-machining accuracy, repeatability and reproducibility. This article presents a generic software solution for minimising these negative dynamics effects, thus improving significantly the laser machining performance across the full range of available processing speeds. In particular, these improvements are achieved by introducing machine-specific compensations in machining vectors to counteract beam deflectors’ inertia regardless of their directions, length and set process speed. An empirical model was developed to obtain data about the actual dynamic response of the beam deflection system across the full range of available processing speeds, and then based on these data, the proposed generic software was implemented into a stand-alone ‘adaptive’ postprocessor. The generation of machine executable part programs is automated, and it is only necessary for the user to enter the selected scanning speeds and beam diameters. Experimental validation was conducted to demonstrate the capability of the proposed software tool. The results demonstrate that substantial improvements can be obtained in machining quality by maintaining a constant pulse distance throughout the machining operations, while the dimensional accuracy is maintained across the available processing speeds without sacrificing the machining efficiency.
This study consisted in investigating parameters that significantly influence the spray efficiency of minimum quantity lubrication in a milling tool with inner channels. An initial experimental approach was used to estimate the oil mist consumption and outlet particle velocities with different inlet pressures, for different shapes of inner channels, without rotation (static part). An experimental versus simulation comparison was undertaken between outlet velocities as a function of inlet pressure. The Reynolds-averaged Navier–Stokes model with the Lagrangian multiphase models was validated by comparing experimental and numerical outlet velocities for different inlet pressures. A numerical rotating tool with inner channels was used with the validated model in the second numerical simulation to analyze the influences of inlet conditions (inlet pressure) based on the tool shape and the rotation velocity, in a dynamic approach. The main objective of the oil mist is to reach the cutting edge (qualifying the minimum quantity lubrication spray efficiency) depending on the inlet conditions (inlet pressures) and the machining configurations (rotation velocities) by analyzing the streamlines of the oil mist particles. The study pointed out the tool design effect combined with its rotation velocity on the oil mist capability to reach the cutting edge. This study offered a trend of parameter sets to provide correct inlet parameters based on machining configurations. At high rotation speed, the inlet pressures needed to be high enough to counter the aerodynamic effects occurred by the tool design.
Existing single spark models are subjected to too simplistic assumptions such as uniform or point heat source, constant plasma radius, invariable materials properties and constant surface temperature during discharge making them far from reality. In this study, more realistic assumptions including Gaussian type distribution of spark heat flux, temperature dependent materials properties, latent heat of melting and expanding plasma channel with pulse current and time have been made to establish a comprehensive modeling platform. The ABAQUS FEM software has been used to simulate the mechanism of crater formation due to a single discharge. The non-uniform thermal flux was programmed through the DFLUX subroutine. The simulation results show that the temperature of work piece decreases as the discharge time increases while the volume of melted and evaporated material increases. A specially designed single spark experimental set-up was developed in laboratory to carry out a few single spark tests for verification purposes. The obtained craters morphologies were examined by optical microscopy and scanning profilometer. It has been shown that the present approach outperforms other previously developed thermal models with respect to cavity outline and size possessing the maximum confirmation errors of 18.1% and 14.1% in predicting crater radius and depth, respectively. Parametric analysis reveals that the melting boundary moves onward by increasing discharge current, whereas it moves back prolonging discharge time. Finally, a closer proximity to experimental material removal rates than those predicted by analytical approach has been recognized which confirms its more precise generalization capabilities towards the real state EDM process.
In this article, the lap joint of acrylonitrile butadiene styrene and polycarbonate is produced by submerged friction stir welding. The objective of this research work is to investigate the effect of welding parameters (rotational speed, traverse speed and plunge depth) on tensile strength. Maximization of weld strength (19.2 MPa) is achieved at a rotational speed of 1500 r/min, traverse speed of 40 mm/min and plunge depth of 1.0 mm. The macrostructure morphology and microstructure are analyzed using the optical microscope and scanning electron microscope. The major defects of the joints are cracks, pores and voids, which are the main reasons for decreasing the tensile strength.
In this study, a new evolutionary approach, Akaike information criterion–based multi-gene genetic programming, is proposed for formulating the functional relationship of wear depth of the laser engineering titanium coatings. The carbon nanotube–reinforced titanium coatings were fabricated with 0, 10, 15, and 20 wt% carbon nanotubes. Six main input process variables such as specimen temperature, friction coefficient, contact potential, gap, carbon nanotube reinforcement composition (%), and sliding distance were considered. The laser cladding process was performed, and a total of 21,600 samples are collected, randomly divided into 17,280 and 4320 sets, and then trained and tested in the proposed algorithm. The performance of the proposed model is compared to that of the artificial neural network model. Statistical evaluation of the models concludes that the proposed model outperformed the artificial neural network. To validate the robustness of the proposed model, sensitivity and parametric analyses are conducted, and the impact of each input variable on the wear depth is studied. Analysis reveals that carbon nanotube reinforcement composition (%) plays a significant role in reducing the wear depth of the laser engineering titanium coatings.
This article considers the problem of scheduling n jobs on m identical parallel processors where an optimal schedule is defined as one that produces minimum makespan (the completion time of the last job) and total tardiness among the set of schedules. Such a problem is known as identical parallel processor makespan and total tardiness problem. In order to minimize makespan and total tardiness of identical parallel processors, improved versions of particle swarm optimization and harmony search algorithm are proposed to enhance scheduling performance with less computational burden. The major drawback of particle swarm optimization in terms of premature convergence at initial stage of iterations is avoided through the use of mutation, a commonly used operator in genetic algorithm, by introducing diversity in the solution. The proposed algorithm is termed as particle swarm optimization with mutation. The convergence rate of harmony search algorithm is improved by fine tuning of parameters such as pitch adjusting rate and bandwidth for improving the solution. The performance of the schedules is evaluated in terms of makespan and total tardiness. The results are analyzed in terms of percentage deviation of the solution from the lower bound on makespan. The results indicate that particle swarm optimization with mutation produces better solutions when compared with genetic algorithm and particle swarm optimization in terms of average percentage deviation. However, harmony search algorithm outperforms genetic algorithm, particle swarm optimization, and particle swarm optimization with mutation in terms of average percentage deviation. In certain instances, the solution obtained by harmony search algorithm outperforms existing clonal selection particle swarm optimization.
One possible way of preventing excessive growth of smearings/loads on the grinding wheel active surface is the introduction of compounds such as sulfur, graphite, or wax into the grinding wheel volume which exerts an active influence on adhesion during the process of impregnation. Limiting the formation of smearings/loads on the grinding wheel active surface is of crucial importance to achieve effective grinding of hard-to-cut materials (such as nickel superalloys) which are characterized by considerable ductility and a strong chemical affinity to abrasive grains, among other things. This article presents the results of experimental tests performed on plunge grinding and the influence of sulfur impregnation of grinding wheels on the smearing/load intensity on the grinding wheel active surface during the process of internal cylindrical plunge grinding of openings made from Inconel® alloy 600 and Incoloy® alloy 800HT®. Bearing steel 100Cr6 was included in the tests as a reference material. Grinding wheels were impregnated with a new method of gravitational sulfurization combined with centrifuging. The experiments carried out show that the adhesive properties of sulfur allowed for considerable limitation of smearing/loading of the grinding wheel active surface with machined material. This mainly concerned limiting the formation of the largest and most technologically undesirable smearings/loads of the intergranular spaces. The presence of sulfur in the grinding wheel volume had a minor influence on the intensity of smearings/loads in the microareas of the active abrasive grains’ apexes. The tests also showed an increase of 32%–49% in the value of parameter Sa in the surfaces ground with grinding wheels impregnated with sulfur for all the examined materials.
For precision mechanical systems, different distribution characteristics of geometric form errors usually lead to different assembly contact states, and in turn, different assembly errors are formed, due to the propagation and accumulation of geometric form errors. Statistically, a batch of part machined by the same precision process possesses the identical distribution characteristics of geometric form errors. It is of great importance to improve assembly accuracy and productivity if the statistic distribution characteristics of geometric form errors can be understood. To solve the problem, two methods of modeling geometric form errors for single parts based on linear combination of basis shapes and modeling statistic geometric form errors for a batch of parts machined by the same process on the basis of principal component analysis are proposed in this article. Besides that, evaluating indicators of model accuracy are also proposed. The results of the case study imply that the two methods can model geometric form errors of single parts and statistically model geometric form errors of a batch of parts, effectively and reliably.
This article developed a three-dimensional finite element model of cryogenic minimum quantity lubrication machining in order to investigate the role of cooling/lubrication effect of cryogenic minimum quantity lubrication in machining of AISI H13 steel. In this model, the cryogenic cooling effect provided by refrigerated compressed air is modeled with a convective heat transfer coefficient. A heat transfer window with the temperature and convective heat transfer coefficient of refrigerated compressed air was defined on tool face and workpiece, respectively, which could move at the same speed as cutting tool so as to simulate continuous cryogenic cooling process of cutting zone under cryogenic minimum quantity lubrication condition. The temperature of refrigerated compressed air was set at –10 °C, –30 °C, –50 °C, –100 °C, and –140 °C to study the influence of cryogenic cooling effect of cryogenic minimum quantity lubrication. Frictional contact between tool and chip was modeled with a simple constant shear stress model. Comparative simulations were conducted under different cooling/lubrication conditions, those are, dry cutting, refrigerated compressed air, and cryogenic minimum quantity lubrication. The simulation results show that both cryogenic cooling effect and lubrication effect resulted in reduction in cutting force and tool temperature when machining AISI H13 steel under cryogenic minimum quantity lubrication condition. With a decrease in temperature of refrigerated compressed air, cutting force and tool temperature did not decrease continuously. The reduction in cutting force, maximum tool temperature, and average temperature of rake face and flank face at low and high cutting speeds was strongly attributed to the cryogenic cooling effect and lubrication effect provided by cryogenic minimum quantity lubrication, respectively. A significant reduction in cutting force and tool temperature was caused by the improvement in lubrication effect provided by cryogenic minimum quantity lubrication irrespective of the cutting speed. The trends revealed by the simulations provide helpful information for the development of this technique.
This work investigates the areal effect, a smoothing of the surface areal topography in measurements from optical instruments that arises from the use of discrete pixels. Two-dimensional and three-dimensional models for the process of acquiring areal topography data were developed and applied to three-dimensional reference surface textures of various traditional machined surfaces that were measured by an atomic force microscope. Sets of reference surface areal data were stitched by a three-dimensional stitching method prior to their use in simulations. Roughness parameters and cumulative power spectra of areal topography of the specimen surfaces measured by coherence scanning interferometry were calculated and compared to the results from the simulated profiles. The results from the simulated data profiles showed good agreement with profiles measured by a coherence scanning interferometry microscope. Finally, the relationship between the pixel size of the optical instruments and the resulting reliability of the high-frequency components of the acquired surface profiles was investigated with spectral analysis. Selection criteria for the magnification of the objective lens are proposed, which allow determination of the appropriate sensor spatial resolution for measurements based on the surface texture characteristics of the specimen.
Friction stir processing is a novel material processing technique. In this study, neural network–based genetic optimization is applied to optimize the process performance in terms of post-friction stir processing mechanical properties of Al7075 alloy and the energy cost. At first, the experimental data regarding the properties (i.e. elongation, tensile strength and hardness) and the consumed electrical energy are obtained by conducting tests varying two process parameters, namely, feed rate and spindle speed. Then, a numerical model making use of empirical data and artificial neural networks is developed, and multiobjective multivariable genetic optimization is applied to find a trade-off among the performance measures of friction stir processing. For this purpose, the properties like elongation, tensile strength and hardness are maximized and the cost of consumed electrical energy is minimized. Finally, the optimization results are verified by conducting experiments. It is concluded that artificial neural network together with genetic algorithm can be successfully employed to optimize the performance of friction stir processing.
This article investigates how to simultaneously optimize both strategic and tactical decisions in the supply chain network design. For this purpose, a bi-level programming model is developed in which supply chain network design problem is considered as a strategic decision in the upper-level model, while the lower-level model contains the assembly line balancing as a tactical decision. In addition, the problem is extended to include push–pull strategy where decisions such as production amount and inventory level of each component in manufacturers are made. Based on the special structure of the model, a heuristic method is proposed to solve the developed bi-level model. A numerical example is employed to show the performance of proposed method in terms of feasibility and convergence. Finally, computational experiments on several problem instances are presented to demonstrate the applications of developed model and the solution method.
An integrated mathematical model was developed to study the thermo-mechanical behavior of strips and work-rolls during warm rolling process of steels. A two-dimensional finite element analysis was first employed to solve for the thermo-mechanical response of the rolled strip under steady-state conditions. The calculated roll pressure and temperature fields were then used to apply proper boundary conditions for solving the governing thermo-mechanical problem for the work-roll. The obtained results indicate that in warm strip rolling of steels, the thermal and mechanical stresses developed within the work-roll are comparable; however, the more significant influence is due to heating and cooling of the work-roll during the process, particularly in case of warm rolling operations of the strips with higher initial temperature. Besides, the utilized model was shown to be capable of determining the effects of various rolling parameters on the thermo-mechanical behavior of strips and work-rolls during warm rolling process.
Scalpel blades are commonly used in surgery to perform invasive medical procedures, yet there has been limited research on the geometry that makes up these cutting instruments. The goal of this article is to define scalpel blade geometry and examine the cutting forces and deflection between commonly used scalpel blades and phantom gel. The following study develops a generalized geometric model that describes the cutting edge geometry in terms of normal rake and inclination angle of any continuously differentiable scalpel cutting edge surface. The parameter of scalpel-tissue contact area is also examined. The geometry of commonly used scalpel blades (10, 11, 12, and 15) is compared to each other and their cutting force through phantom gel measured. It was found that blade 10 displayed the lowest average total steady-state cutting force of 0.52 N followed by blade 15, 11, and 12 with a cutting force of 1.17 N (125% higher than blade 10). Blade 10 also displayed the lowest normalized cutting force of 0.16 N/mm followed by blades 15, 12, and 11 with a force of 0.19 N/mm (17% higher than blade 10).
This article focuses on experimental investigation and effective approach to optimize the milling characteristics with mono and multiple response outputs such as vibration signals, cutting force, and surface roughness. To achieve this goal, experiments were designed based on Taguchi’s L18 (21 x 33) orthogonal array. During the milling of AISI 1050 steel, process performance indicators such as vibration signals (RMS), cutting force (Fx), and surface roughness (Ra) were measured. The effect of process parameters such as depth of cut, feed rate, cutting speed, and number of insert on RMS, Fx, and Ra were investigated and parameters were simultaneously optimized by taking into consideration the multi-response outputs using Taguchi-based gray relational analysis. Taguchi’s signal-to-noise ratio was employed to obtain the best combination with smaller-the-better and larger-the-better approaches for mono- and multi-optimization, respectively. Analysis of variance was conducted to determine the importance of process parameters on responses. Mathematical models were created, namely, RMSpre, Rapre, and Fxpre, using regression analysis. According to the multi-response optimization results, which were obtained from the largest signal-to-noise ratio of the gray relational grade, it was found out that the optimum combination was depth of cut of 1 mm, feed rate of 0.05 mm/rev, cutting speed of 308 m/min, and number of insert of 1 to minimize simultaneously RMS, Fx, and Ra. It was obtained that the percentage improvement in gray relational grade with the multiple responses is 42.9%. It is clearly shown that the performance indicators are significantly improved using this approach in milling of AISI 1050 steel. Moreover, analysis of variance for gray relational grade proved that the feed rate is the most influential factor as the minimization of all responses is concurrently considered.
A large aircraft fuselage panel is commonly composed of a variety of thin-walled components. Most of these components are large, thin and compliant, and they are also prone to some flexible deformation during assembly and remain deformed after assembly. Besides, many different fabrication and assembly manners are adopted in order to guarantee the complicated assembly relationships between each component. The above characteristics often cause large aircraft fuselage panels to exhibit low stiffness and weak strength, thereby inducing deformation during assembly. Since the posture of a large aircraft fuselage panel is commonly evaluated by matching the theoretical and actual positions of the measurement points placed on it, and its assembly deformation is also represented by the position errors of the measurement points, a reasonable measurement point placement is significant for the large aircraft fuselage panel in digital assembly. This article presents a method based on the D-optimality method and the adaptive simulated annealing genetic algorithm to optimize the placement of the measurement points which can cover more deformation information of the panel for effective assembly error diagnosis. By taking the principle of the D-optimality method, an optimal set of measurement points is selected from a larger candidate set through adaptive simulated annealing genetic algorithm. As illustrated by an example, the final measurement point configuration is more effective to maximize the determinant of the corresponding Fisher Information Matrix and minimize the estimation error of the assembly deformation than those obtained by other methods.
Data for processing of micrometric geometric features via electro-discharge machining are not widely available. This article describes a methodology to produce microfeatures with a low-cost, open-architecture micro-electro-discharge machining setup using a Resistive–Capacitive oscillator as the power source. The goal of this work was to identify process condition parameter values to maintain a stable micro-electro-discharge machining process. The setup consists of a machine under development for the fabrication of two-and-a-half-dimensional microstructures on conductive materials, using 254-µm-diameter brass electrodes. Three performance parameters were defined to characterize the process: material removal rate, ratio of electrode to workpiece wear, and surface finish. Because of their relevance to the viability of the process, voltage and energy were selected as controllable parameters. The effect of controllable parameters on the mean and standard deviation of the performance parameters during machining of an A36 cold drawn steel workpiece was studied. Voltage and energy values that resulted in a stable process were identified from this exploratory study. Microchannels of 290 µm width (discharge over cut of 18 µm on lateral walls), 50 µm depth and various millimeters long were machined to test selected values. Microchannel depth was maintained constant by applying a sloped motion that compensated for electrode wear.
This article provides a literature review of finite element simulation studies for metallic powder bed additive manufacturing processes. The various approaches in the numerical modeling of the processes and the selection of materials properties are presented in detail. Simulation results are categorized according to three major findings’ groups (i.e. temperature field, residual stresses and melt pool characteristics). Moreover, the means used for the experimental validation of the simulation findings are described. Looking deeper into the studies reviewed, a number of future directions are identified in the context of transforming simulation into a powerful tool for the industrial application of additive manufacturing. Smart modeling approaches should be developed, materials and their properties should be further characterized and standardized, commercial packages specialized in additive manufacturing simulation have to be developed and simulation needs to become part of the modern digital production chains. Finally, the reviewed studies are organized in a table and characterized according to the process and material studied, the modeling methodology and the experimental validation method used in each of them. The key findings of the reviewed studies are also summarized.
The demand for miniaturized components is on the rise, especially from the biomedical and aerospace industry. As a result, there is a strong research potential towards the micro-manufacturing of biomedical and aerospace components. Titanium-based alloys are known for their biocompatibility and high strength-to-weight ratio, making them most suitable for such applications. In this research, flank wear progression, surface roughness and side burrs, the basic performance parameters of a typical micromachining operation, are presented and analysed through analysis of variance in order to determine the key process parameters. It was found that micromachining can be classified into two categories: micromachining with undeformed chip thickness below the tool edge radius and micromachining keeping the undeformed chip thickness above the tool edge radius. The results showed that when machining with undeformed chip thickness above edge radius, the feedrate remains the most significant parameter affecting tool wear (41% contribution ratio), surface roughness (83%) and burr width (80%). This result places this type of machining closer to macro-machining where feed contribution was found to be 69%, 92% and 75% as against micromachining below edge radius, where contributions stood at 17%, 53% and 52% on tool wear, surface roughness and burr width, respectively. The results underscored the importance of considering the tool edge radius in micromachining.
In this research, the rheological properties and flow behaviour of M2 high-speed steel have been investigated in low and high solid fractions by compression and rheometry tests. First series of experiments were started by partial remelting of rolled-annealed M2 billet in an argon-controlled atmosphere and holding for an appropriate time to obtain a globular microstructure and then conducting the rapid compression test on the prepared sample. Load versus deformation data were recorded using a high-frequency data acquisition system during the tests. Deformation mechanism of the semi-solid steel alloy and its correlation to rheological properties were then investigated. In the second series of experiments, the material was sheared continuously while cooling down from liquidus state to a semi-solid temperature. The rheology tests were performed using a self-developed concentric cylindrical viscometer under different cooling rates (25 °C/min–35 °C/min) and shear rates. The results revealed that when solid fraction exceeds about 40%, the viscosity increases suddenly and reaches a viscosity of about 20 Pa s. This solid fraction is a critical point when designing the process for industrial applications such as thixocasting.
In this research study, a comparative examination on the mechanical properties of AA6063 has been carried out after having been processed by isothermal forging, using plane-shape dies and starting from different initial deformation states. It introduces the novelty of employing experimental data obtained from the isothermal forging so as to model the flow rules of AA6063 processed by equal channel angular pressing taking temperature into account and using artificial neural networks to this end. Subsequently, these flow rules are employed to model the behaviour of AA6063 by means of finite element simulation. Furthermore, a validation of the experimental results is made with those obtained from the simulations using the flow rules attained with the neural networks. It is shown that it is possible to achieve higher precision than with traditional fitting methods of flow rules. In addition, this study presents the novelty of carrying out a comparative study between different starting material states, prior to forging, including among these material previously processed by the severe plastic deformation process, which is referred to as equal channel angular pressing. Moreover, the experimental results obtained when processing the aluminium alloy by equal channel angular pressing are compared to those states, which correspond to the traditional way of working on aluminium alloys, which can be quenched and aged for the purpose of improving their mechanical properties.
The probabilistic design system is introduced for the sensitivity analysis to analyze the effects of machining parameters during electrical discharge machining process. An axisymmetric finite element thermal model is presented to investigate the electrical discharge machining process. By comparing the discharge crater geometry for the finite element method results and experiment results under different conditions, the deterministic thermal model is proved to be validated. Monte Carlo simulation method and response surface method are both used in the sensitivity analysis. Parameters of discharge voltage, peak current, pulse-on time and discharge channel radius are selected as the design variables. The sensitivity analysis results meet the confidence limit of 0.95. It is concluded that the discharge voltage and peak current have significant influences on the electrical discharge machining process, whereas the pulse-on time and discharge channel radius have little influence. Moreover, the increase in discharge channel radius can reduce the material removal rate. The increase in other parameters can increase the material removal rate.
This article proposes an approach to minimize the surplus parts in selective assembly with genetic algorithm. A grouping method is proposed considering the different tolerance ranges of parts, and the effect of part group assignment on assembly success rate is investigated. Based on the grouping method, a genetic algorithm with a specially designed two-dimensional chromosome structure is proposed to minimize surplus parts, and the fitness function of the solution and the constraints to be satisfied in the evolution process are investigated. The proposed selective assembly approach with the corresponding grouping method is further improved for the product assembly with multiple dimension chains. Through case studies, it is verified that the proposed approach is more competitive to improve the product assembly success rate and reduce the surplus parts.
Investment casting process produces high-precision castings, but there is a constant demand for improving the process capabilities, including dimensional accuracy and consistency. In this article, a state space modeling approach of investment casting process for dimensional variation is developed. This research focuses on the linear dimensional change (expansion or shrinkage) in the investment casting process. The generation, propagation and accumulation of the dimensional variation in the investment casting process are interpreted. In order to develop a mathematical model to describe the procedure above, a notion, the dimensional variation stream, is employed, and several key concepts, such as dimensional change rate, state vector and process parameter variation vector, are defined. The inherent relationships among these components are uncovered and finally bring about a State Space Model that describes the dimensional variation stream in the whole investment casting process. In the end, the usages of the developed model are illustrated and summarized via studying a case.
From the last few decades, vibratory welding techniques have been used for improving the mechanical properties of weldments. Previous results showed that welded test specimens under vibratory conditions exhibited improvements in mechanical properties than the conventional arc welding. In this present work, vibratory set-up has been developed for inducing mechanical vibrations during welding operation. The designed vibratory set-up produces the required frequency with amplitude and acceleration in terms of voltages. In the current investigation, weld specimens were prepared while varying the two input parameters: voltage and time of vibration. And the remaining process parameters such as travel speed, current, and other electrode parameters were kept constant. Metallurgical properties showed that refined microstructure has been achieved for the vibratory welded specimens. The refined grain structure is responsible for the improvement in flexural strength, ultimate tensile strength, impact strength, and hardness of the vibratory weld pieces.
In this article, a grey–fuzzy-based algorithm with the Taguchi method is proposed to find the optimal process parameters’ setting for submerged arc welding process of AISI 1518 grade steel on the multiple performance characteristics such as tensile stress, toughness and hardness of weldment. Various process parameters, such as wire feed rate, stick out and traverse speed of welding process, were exposed by investigation. The proposed algorithm, coupling the grey relational analysis with the fuzzy logic, obtains a grey–fuzzy reasoning grade to evaluate the multiple performance characteristics according to the grey relational coefficient of each performance characteristic. Through the grey–fuzzy logic analysis, the optimization of multiple performance characteristics can be converted into the optimization of a single grey–fuzzy reasoning grade. Finally, the process parameters are optimized by the Taguchi method. The optimal process parameter combination becomes Wf-3 So-1 Ts-3, that is, the wire feed rate at level 3 (2 m/min), stick out at level 1 (20 mm) and traverse speed at level 3 (0.9 m/min) for maximum tensile stress and toughness and minimum hardness of weldments. It is also observed stick out on the overall mechanical property is more significant compared with other welding parameters (wire feed rate, traverse speed).
The effect of various wire electrical discharge machining process parameters such as pulse on time, pulse off time, pulse current and the wire drum speed on machined surface quality characteristics such as surface roughness and kerf width has been discussed. The experiments were carried out with L27 orthogonal array on hybrid metal matrix composite prepared by inert gas–assisted electromagnetic stir casting process using particulates 7.5% Al2O3 and 7.5% SiC each in Al7075 alloy. Taguchi-based grey relational analysis, a multi-response optimization technique, was used to find the optimal process parameter setting for the best quality machined characteristics. Results of analysis of variance showed that the order of significance was pulse on time, pulse current, pulse off time and the wire drum speed contributing 50.02%, 39.50%, 4.58% and 2.75%, respectively, while machining the hybrid composite. Confirmation test was carried out at selected optimal parameter setting, which showed improvement in grey relational grade, thus confirming the robustness of grey relational analysis.
Variation modeling of sheet metal assemblies is quite critical when specifying and verifying the geometric and dimensional requirements of parts. However, sheet metal parts’ compliant behavior makes the variation modeling approach more complex when coupling both rigid variation in the in-plane direction and compliant variation in the out-of-plane direction. In order to completely model the overall three-dimensional variation of sheet metal assembly, a unified variation modeling approach considering both rigid and compliant variations is proposed in this article. Four types of coordinate systems are defined. In the in-plane direction, homogeneous transformation matrix is used to describe the position and orientation relationships between assembly elements, and differential motion vector is used to represent rigid variation. In the out-of-plane direction, a vector composed of the deviations of selected key characteristic points is used to represent compliant variation, and the method of influence coefficients is adopted to analyze compliant variation. The overall three-dimensional variation of sheet metal assembly is the superposition of both in-plane rigid variation and out-of-plane compliant variation. Three types of variation sources that are fixture locators’ deviations, datum features’ deviations and joint features’ deviations are considered here. A case study is presented to illustrate the proposed approach.
Conventional metal cutting processes involve massive consumption of energy where the specific cutting energy is usually high. A major division of this energy is converted into heat, which creates detrimental effects on cutting tool wear, surface quality of machined workmaterial and dimensional accuracy. Although cutting fluids are effective to coerce this energy transfer, the growing challenge to deal with the environmental and health aspects stood by coolant machining is imposing manufacturers to limit the usage of cutting fluids in current metal cutting practice. This research work introduces a new cutting tool, namely, electrostatic micro-solid lubricant–coated carbide tool with molybdenum disulfide as a solid lubricant. To exploit efficacies of newly developed electrostatic micro-solid lubricant–coated cutting tools in comparison with the uncoated cutting tools in machining processes, cutting forces, tool wear, chip formation and surface finish of machined workmaterial have been practically investigated. The results revealed that electrostatic micro-solid lubricant–coated tools performed much better as compared with that of machining with uncoated tools, and the adeptness of the electrostatic micro-solid lubricant–coated tools can make a potential alternative with additional benefits of being able to accomplish sustainable machining.
The discharge gap phenomena in powder-mixed electrical discharge machining are examined using SiC powder mixing in water dielectric liquid. Surface modifications on machined work materials are investigated by means of optical, scanning electron microscopy and energy-dispersive spectroscopy. The experimental studies revealed that the surface morphology drastically affected the additives as means of secondary discharges and particle migration from dielectric liquid. Such mechanisms do not occur randomly and indicate a robust dependency with respect to powder suspension concentration, pulse on duration and current. The influence on discharge transitivity with respect to suspended particle concentration is noted with pock shape development due to secondary discharges followed by an intermediate stage signifying a sudden increase in particle migration from the dielectric liquid. The particles decomposed on the surface at specific operational conditions demonstrating the possibility of methodical surface alloying using the process. Finally, the mechanisms involved were elaborated with respect to operational parameters and discussed based on the experimental results.
This article presents an important investigation of material removal mechanism in grinding utilizing single grit scratch tests. The investigation helps people to understand the abrasive cutting behaviour when the abrasive cutting edge shape alters during single grit grinding. The results provide fundamental knowledge of the grinding material removal process, which helps to improve grinding performance and quality. Cubic boron nitride grits of 40/50 mesh size were used to perform scratch tests on the alloy Inconel 718. The concepts of material pile-up ratio and actual material removal area were introduced to measure the material removal efficiency during grinding. It is found that pile-up ratio decreases and actual material removal area increases when the depth of cut increases, albeit the material removal mechanism is highly dependent on the abrasive grit cutting edge shape. The material removal mechanism along the scratch length shows different behaviours at the entrance and exit sides of the scratching passes. When a grit was moving along its scratch path, it pushed material forward resulting in high material accumulation at the exit side of the scratches. Consequently, cutting is more prominent at the entrance side of the scratch, whereas ploughing or pile-up is extremely high at the exit side of the scratches. The research finding provides crucial information for grinding process optimization.
The transfer of elements C, Si, Mn, P and S from slag into the weld metal or from weld metal into the slag and microhardness has been studied using formulated fluxes. The fluxes have been formulated using extreme vertices design with an aim to develop mathematical models for change in element content and mechanical properties versus flux constituents for submerged arc welding of high-strength low-alloy steel. It is found that CaO is the most significant flux constituent and Al2O3 is the second most significant constituent among individual mixtures. CaO·MgO and CaO·Al2O3 among binary mixtures have significant effect on element transfer and microhardness. Developed mathematical models have been checked for adequacy using t-test and analysis of variance (F-test). Flux mixtures’ composition has been provided for optimum chemical composition and mechanical properties. One of the optimum flux mixture with composition, CaO 11.61, Al2O3 12.33, CaF2 15.00 and MgO 39.06, would be providing desirable chemical composition and mechanical properties.
In modern manufacturing system, tool condition is one of the important factors which affects the machining under various cutting conditions, and the tool has to be replaced when it was worn out. The objective of this work is to estimate the effect of various input cutting parameters on tool life in boring of steel (AISI 1040) by finding the roughness on machined surface and amplitude of workpiece vibration. The input parameters used are cutting speed, feed rate and tool nose radius. According to design of experiments, 18 experiments were conducted on computer numerical control lathe by changing cutting parameters. Most of the researchers have used accelerometers to measure vibration of cutting tool in machining process. In this work, a new attempt was made with laser Doppler vibrometer for online data acquisition of workpiece vibration, and a high-speed fast Fourier transform analyzer was used to process the acousto-optic emission signals obtained from laser Doppler vibrometer. It was found that it is easy to measure vibration of workpiece in less time with laser Doppler vibrometer. The data were analyzed with Taguchi and analysis of variance for a significant parameter. Contribution of individual cutting parameters on surface roughness and amplitude of workpiece vibration is calculated with the analysis of variance.
Laser bending is a nontraditional forming process, where sheet metal gets plastically deformed by laser-induced thermal stresses. The objective of this study is to establish the relationships between bending angles and process parameters in a pulsed laser bending process using soft computing–based methods, that is, neural networks and neuro-fuzzy system. Laser power, scan speed, spot diameter and pulse duration were considered as inputs, and bending angle was taken as output for modeling the bending angle (called forward analysis). In the case of inverse analysis or process synthesis (i.e. to determine the process parameters in order to achieve the desired outputs), bending angle and pulse duration were considered as inputs, and laser power, scan speed and spot diameter were treated as outputs. For both forward and inverse analyses, neural networks and neuro-fuzzy systems were trained in a batch mode with experimental data using two different algorithms, that is, genetic algorithm and back-propagation algorithm. The optimized networks were used for the predictions of bending angles and process parameters for some test cases. All the developed models were found to be satisfactory for both the analyses. Genetic algorithm was found to perform better than the back-propagation algorithm for both the networks in terms of prediction accuracy but at the cost of computational time. Neural networks trained with genetic algorithm were seen to perform better than the other models in predicting bending angles and process parameters. The developed models might be helpful in automating the pulsed laser forming process.
This article deals with an economic production quantity inventory model for non-instantaneous deteriorating items under inflationary conditions, permissible delay in payments, customer returns, and price- and time-dependent demand. The customer returns are assumed as a function of demand and price. The effects of time value of money are studied using the Discounted Cash Flow approach. The main objective is to determine the optimal selling price, the optimal length of the production period, and the optimal length of inventory cycle simultaneously such that the present value of total profit is maximized. An efficient algorithm is presented to find the optimal solution of the developed model. Finally, a numerical example is extracted to solve the presented inventory model using our proposed algorithm, and the effects of the customer returns, inflation, and delay in payments are also discussed.
Conventional forming limit diagram concept to determine the forming severity in tube hydroformed products might be restrictive because materials experience complex stress and strain path changes during the shaping process. In this study, a polar effective plastic strain diagram approach was adopted as a strain path–insensitive measurement to establish a criterion for evaluation of necking and, consequently, bursting failures in the tube hydroforming process. The polar effective plastic strain–based failure prediction uses information of the effective plastic strain and the direction defined by the arctangent of the current strain-rate ratio. These values were measured and calculated from free-expansion tests of straight AA6063 tubes for various combinations of axial feed and internal pressure using a stereo vision-based surface strain measurement system. The polar effective plastic strain diagram was constructed and applied to finite element analysis to predict the forming limit of AA6063 tubes. The effect of pretensions was also considered.
GH4169 is comparatively a new superalloy mainly used as turbine components because of its outstanding combination properties such as high-temperature strength, thermal stability and wear resistance. But these also make it hard to cut, and its machined surface quality and integrity are particularly sensitive to the manufacturing process employed. The existing researches on machining-induced surface integrity and machinability of hard-to-cut materials are briefly reviewed; the effects of processing parameters on surface integrity for GH4169 components are studied in detail via orthogonal-designed external grinding experiment. The single-factorial plain grinding experiment was designed to further investigate the influence of depth of cut on the surface integrity characteristics. The surface roughness, residual stress distribution, microhardness profile and microstructural alteration within the subsurface were obtained and analyzed. It was shown that the surface integrity is susceptible to the magnitude of depth of cut, and the components ground with low depth of cut are of more acceptable surface quality with less variation in residual stress and microhardness within the machining-affected layer than those obtained with high depth of cut. No severe microstructural alteration or adverse surface cracking was discerned when the depth of cut is reasonably set.
This article presents a model within the sustainable machining paradigm. In general, the optimization of machining process for the minimum energy consumption alone does not have sufficient impetus for application in the manufacturing companies wherein profit maximization remains the preferred mode of operation. In this study, a novel objective function for the optimization of machining process is modelled which determines the optimal machining parameters for the maximum profit per unit energy consumption. The model is applied to an example problem of a single-pass turning operation and is found unique from the past models focused on the minimization of either energy consumed or cost incurred.
Three grades of titanium alloy Ti (grade 2), Ti-6Al-4V (grade 5) and Ti-5Al-2.5Sn (grade 6) were machined using electric discharge machining after deep and shallow cryogenic treatment. The peak current was observed to be the most significant factor followed by electrode material and pulse-on time. Subsequently, a mathematical model for predicting material removal rate of titanium alloys was developed using dimensional analysis based on the significant process parameters affecting material removal rate and the thermal–physical properties of the titanium alloy. The predicted results obtained from the mathematical model were validated by comparing with the experimental results and were found to be in good agreement with each other. Incremental increase in material removal rate was observed after deep cryogenic treatment due to increase in thermal and electrical conductivity of the material. The model showed that the thermal properties of the material such as thermal conductivity, specific heat and boiling point of materials affect the erosion process in electric discharge machining. Microstructure analysis was carried out using scanning electron microscope, energy-dispersive X-ray spectrometer and X-ray diffraction for selected samples. The migration of different elements and formation of compounds on the machined surface was investigated using energy-dispersive X-ray spectrometer and X-ray diffraction analysis.
The process capability of die-less hydroforming for producing tubular structures of complex geometries was investigated. Multi-lobe tubular structures were chosen for this study as they are capable of carrying higher loads than normal tubes of the same weight. The forming characteristics of three variants of tubular geometry with longitudinal lobes, circumferential lobes, and helical lobes were studied through numerical analysis. The parameters that were investigated were tube wall thickness, tube diameter, tube length-to-diameter ratio, pressure loading paths, and lobe-forming patterns. The finite element analysis showed that the length of the tube does not influence the lobe formation for all three tube variants. The finite element analysis results also demonstrated that lobe wall thinning varies linearly with hydroforming pressure for all multi-lobe tube patterns studied. The strength-to-weight benefit of the tubular structures was also verified through finite element analysis for annealed stainless steel tube sample of 200 mm length, 40 mm diameter, and 2 mm wall thickness. The longitudinal lobed geometry, circumferential lobed geometry, and the helical lobed geometry all were able to carry significantly larger loads as compared to a blank tube of the same mass under compressive, flexural, and torsional loading conditions. To test the viability of the die-less hydroforming process, a longitudinal lobed tubular structure was fabricated and formed. The results from this study indicate that a die-less hydroforming manufacturing process is viable and capable of producing strong, lightweight parts of complex geometries. Besides being capable of producing complex tubular structures, the costs associated with die-less hydroforming are significantly lower due to the absence of a press and dies. However, preparation of tubular blanks requires reliable weld seams and rolling operations.
A complex system, be it a manufacturing system or otherwise, is prone to abnormal functioning, as its units or elements experience unpredictable functional variation. Determining the likely root causes of its undesirable functional events is required to carry out cause analysis of the system from functional point of view. Although the manufacturers provide some information in the manual in this regard, yet these are not conclusive and fall much short in guiding the users in functional cause analysis. Structure plays an important role in this objective. In this article, a procedure for functional cause analysis of a complex manufacturing system through structure is presented using digraph models. ‘Function event digraph’ is defined for a complex manufacturing system at its various hierarchical levels by considering its input and output functions and their interrelations. A top or undesired functional event for the system is identified from its digraph model, and its root causes are obtained by developing ‘functional cause analysis tree’. The suggested approach helps designers and practicing engineers in functional cause analysis of manufacturing systems and thus leading to reliability enhancement and sustenance. An example of a complex CNC (computer numerical control) grinding machine is illustrated to demonstrate the methodology.
Simple shear, uniaxial tension–compression and bending tests were used to determine the cyclic behaviour of two sheet metals: DP600 and AKDQ. The Yoshida–Uemori two-surface model along with Hill’s quadratic yield function was used to simulate the behaviour of these two materials in each test. For each test, a set of material constants was identified such that the error between the simulated and experimental responses is minimized. Using the material constants obtained from one test, the other tests were simulated to see whether the set of constants obtained from this test is able to describe the material response in the other tests. The results show that depending on the material, the set of constants obtained from one test may or may not be able to reproduce the material response in the other tests. Finally, each set of constants was used to simulate the springback of a U-shaped part formed in a channel draw process. The predicted springback profiles obtained from each set of constants were compared with the experimental profile. It was found that all three tests are suitable to characterize the behaviour of DP600 sheets in view of predicting the springback of channel sections. For AKDQ, however, the error between the predicted and experimental springback profiles was significant regardless of the type of characterization test performed. But for this channel draw process, simulations based on material data obtained from the reverse bending test provided the best prediction of springback.
Continuous improvement of the component roundness accuracy through computer numerical control centreless grinding in high productivity is one of the most important issues particularly for modern automotive and bearings manufacturing. For instance, the process is towards 0.1–0.3 µm roundness accuracy in grinding the engine valve rod because of the increasingly stringent energy efficiency requirement in automotive engines. The characteristics of the computer numerical control centreless grinding process make it challenging, that is, how to assure the workpiece roundness generation in a predictable, producible, highly productive and scientific manner. In this article, a simulation-based industrial feasible approach is presented to model and control the workpiece roundness generation and its perfection strategies in computer numerical control centreless grinding. The kinematics of the workpiece in the process is presented according to the workpiece profile and its geometric configurations. Taking into account the workpiece geometric movements, contact and loss effect and grinding restrictions, a time-domain dynamic model is developed to provide the dynamics description of the workpiece, the grinding wheel and the control wheel in the process. The roundness generation of the workpiece is further predicted using this model. The effects of multiple factors on the workpiece rounding process are discussed and the influences on final roundness errors are investigated.
When using magnesium for industrial-scale production, a series of aspects must be taken into consideration, such as the ignition risk (due to magnesium reaction with water resulting hydrogen), the cooling fluids representing up to 16%–20% of the manufacturing costs as well as being environmentally harmful and the costs of waste disposal. Therefore, the selection of an adequate cooling system is a very important factor, which may eliminate all the above-mentioned disadvantages. This research investigates the influences that cooling systems have on surface quality of magnesium alloy parts. An experimental analysis for milling operations was carried out using three cooling methods: dry cutting, minimum quantity lubrication and compressed air. Surface quality was assessed according to three aspects: surface roughness, material microhardness and residual stress variation. A statistical analysis of the results was performed in order to emphasize the effects of the machining parameters and cooling methods on surface quality. Furthermore, an adaptive neuro-fuzzy inference system, capable to predict surface roughness based on machining conditions, was developed. A very good agreement was found between the experimental values and the estimated ones. The results have shown that in general, the minimum quantity lubrication cooling system generates a superior surface quality compared to other systems.
The pillow is a defect that adversely affects the geometrical accuracy as well as the formability in single-point incremental forming. With a main objective to control this defect, the effects of mechanical properties of material on pillowing are examined in this work. To identify the mechanical property that significantly affects pillowing, single-point incremental forming tests are conducted using a variety of materials (i.e. 11). It is found that a property (i.e. area reduction at tensile fracture) that controls the formability of a material in single-point incremental forming does not have any significant effect on its pillowing tendency. Interestingly, hardening exponent (i.e. a property that has controlling influence on the stretch-ability of material) appears to be the most influential property that determines the pillowing tendency of sheet metals in single-point incremental forming. Furthermore, the pillowing tendency of a material decreases with the decrease in this particular property. This, according to finite element analysis, occurs because strain localization around the tool/sheet contact correspondingly increases. To select and rank materials with respect to the pillowing behavior, a formula describing the property–pillowing relationship is proposed. As a secondary objective, the correlation between pillowing and forming depth is also investigated in this work. It is shown that initially the pillow progresses as the forming depth increases. However, after forming has been carried out to a certain depth, the pillow begins to regress, most likely due to strain hardening of sheet metal. In conclusion, it is suggested to lower the hardening exponent of sheet metals in order to control pillowing in single-point incremental forming.
Three-dimensional rolling is a novel forming process for three-dimensional surface parts, which combines the rolling process with multi-point forming technology. This process employs a pair of forming rolls as a forming tool; the residual stress of sheet metal makes the sheet metal generate three-dimensional deformation by controlling the nonuniform distribution of roll gap of the forming rolls. In this article, two types of forming processes are investigated for three-dimensional surface parts with the same target shape in different roll adjusting radius. The roll adjusting radius of a forming process is much larger than the target transverse curvature radius of the forming part, and the roll adjusting radius of another forming process is equal to the target transverse curvature radius of the forming part. Finite element analysis models are established; spherical and saddle surfaces are simulated. The corresponding experimental results are obtained. The dimensional accuracy of the forming parts using the two types of forming processes is compared, and the difference between the two types of forming processes for forming parts is analyzed through simulated results. The bendable roll rotates around its bent axis easily if its bending deformation is small; therefore, the forming process that the roll adjusting radius is much larger than the target transverse curvature radius of the surface part has relatively extensive application prospect. The comparison and analysis of the forming results may provide useful guidance on optimizing the three-dimensional rolling process for three-dimensional surface parts.
Electrical discharge machining is commonly used in manufacturing industry to make dies of complex cavities. This work investigates electric discharge machining of PH17-4 stainless steel when both graphite powder–mixed and surfactant-mixed dielectric fluid were used during electrical discharge machining. Taguchi method is used for conducting experiments with L9 orthogonal array by choosing electrical discharge machining process parameters, namely, peak current, surfactant concentration and graphite powder concentration. The process performance characteristics of electrical discharge machining such as material removal rate, surface roughness and tool wear rate are chosen for this study. The purpose of this work is to find significance of process parameters on performance characteristics and also get an optimal combination of these parameters using Taguchi-data envelopment analysis–based ranking multi-response optimization method.
In order to reduce serious tendency of the shrinkage porosity in ZL205A alloy, the design of experiment technique, Taguchi method is introduced to optimize the process parameters of cylindrical shell ZL205A alloy parts produced by low-pressure die casting in this article. The effect of pouring temperature, filling time and packing pressure on the shrinkage porosity in ZL205A castings is investigated using the orthogonal array and Advanced Porosity Model in ProCAST to calculate the volume of shrinkage porosity. The effectiveness of selected casting parameters in reducing the shrinkage porosity in cylindrical shell ZL205A casting is verified through analysis of signal-to-noise ratio and analysis of variance. Numerical results indicate that the optimized process parameters, including a pouring temperature of 725 °C, filling time of 20 s and packing pressure of 175 kPa, can be used to reduce the formation of shrinkage porosity in ZL205A castings.
In this study, an attempt has been made to statistically model the relationship between cutting parameters (speed, feed rate and depth of cut), cutting force components (Fx, Fy and Fz) and workpiece absolute surface roughness (Ra). The machining case of a martensitic stainless steel (AISI 420) is considered in a common turning process by means of a chemical vapor deposition–coated carbide tool. A full-factorial design (43) is adopted in order to analyze obtained experimental results via both analysis of variance and response surface methodology techniques. The optimum cutting conditions are achieved using mutually response surface methodology and desirability function approaches while the model adequacy is checked from residual values. The results indicated that the depth of cut is the dominant factor affecting (Fx: 86%, Fy: 58% and Fz: 81%), whereas feed rate is found to be the utmost factor influencing surface roughness behavior (Ra: 81%). In addition, a good agreement between the predicted and measured cutting force components and surface roughness was observed. The results are also validated experimentally by determining errors (Fx: 6.51%, Fy: 4.36%, Fz: 3.59% and Ra: 5.12%). Finally, the ranges for optimal cutting conditions are projected for serial industrial production.
Vibrations are one of the obstacles to productivity of machining process since their presence reduces surface quality, dimensional accuracy and tool life. This article proposes a vision-based approach for determining vibration level in metal cutting. Vibration level of cutting tool is controlled by changing the tool overhang, and the resulting irregularity of surface texture is used as a criterion for determining the cutting tool vibration. Undecimated wavelet transform is used to decompose the surface image of the workpiece into sub-images in which the cutting tool vibration can be indicated. The texture of the preferred sub-image is analyzed using gray-level co-occurrence matrix texture features. In order to validate the proposed vision-based method, an accelerometer was attached to the shank of the cutting tool to measure vibrations in tangential direction. The experimental results showed that the combination of undecimated wavelet decomposition and gray-level co-occurrence matrix texture features can be used as a robust method for determining vibration level in the turning process.
The advanced high-strength steels have become an interesting alternative in automotive industry to reduce vehicle weight and therefore reduce fuel consumption. However, its wide application in the automotive industry is still limited due to challenges in formability, tool life and springback. The springback is pointed out in literature as the main problem that involves the mass production of structural components, and the aspects that show influence are still not fully understood. This work aims to statistically analyze the influence of process and tool parameters on the magnitude of the springback on five high-strength steels. In order to do so, the U-bending test was used and two process parameters and two tool parameters that are mentioned in the literature as the most influential were chosen. The results of the analysis of variance pointed out the influence of the blank holder force as the parameter of greatest influence on springback, followed by the tool radius and friction condition.
Process capabilities, which are the outcomes of both Critical Success Factors and Barriers, could play an essential part in the implementation and continuous development of a process. This article explores the Configuration Management process capabilities extracted on the basis of semi-structured interviews with Configuration Management professionals and analysis of two highly significant studies in the development of Configuration Management as a researchable topic. The first study investigated the Critical Success Factors for successful Configuration Management development, while the other study looked at the identification of barriers to effective Configuration Management deployment. It is evident that the majority of research studies on process maturity concepts have focused on process capability itself, not the success or failure of Configuration Management. A list of 10 process capabilities and 35 constructs (C1–C35) are established which would provide necessary foundation for the effective implementation of CM practices.
This work investigates the effects of cutting parameters on surface roughness (Ra, µm), cutting temperature (T, °C) at the chip–tool interface and the material removal rate during hard machining of AISI 1015 (43 ± 1 HRC) steel using carbide insert under dry and spray impingement cooling environment. A combined technique using orthogonal array and analysis of variance was employed to investigate the contribution of spindle speed, feed rate, depth of cut and air pressure on responses. It is observed that with spray impingement cooling, cutting performance improves compared to dry cutting. The predicted multi-response optimization setting (N3-f1-d1-P2) ensures minimization of surface roughness, cutting temperature and maximization of material removal rate.
In industrial manufacturing applications to improve the surface quality of cylindrical parts such as valves, pistons of hydraulic or pneumatic cylinders, pump shafts and bearing bores, some surface-finishing processes such as grinding, super finishing and honing are applied. Nevertheless, none of them provides to improve fatigue, wear and corrosion resistance. Shot peening and case hardening can improve these properties, but they are expensive and application of them takes more time. Burnishing can increase the surface hardness by generating compressive stresses on the surface and as a result, it improves fatigue and corrosion resistance in addition to providing better surface quality. Roller burnishing is a very simple and very low consumption power process and can be applied on a conventional or computer numerical control lathe. The effect of the burnishing parameters on the surface quality and the burnishing force were examined with experimental study. The experiments were carried out using AISI 1040 carbon steel material. It was concluded that the burnishing feed is the most significant factor affecting the surface quality. Experimental results were tested with analysis of variance.
An investigation of the micro-channelling process on a quartz crystal using an abrasive slurry jet is presented. An experimental study is conducted first to understand the material removal process, surface quality as well as the effect of process parameters on the channelling performance, namely the material removal rate, channel depth, top channel width and channel wall inclination angle. It is found that a good micro-channel top edge appearance and bottom surface finish can be produced on quartz crystal by employing smaller particles with a relatively small jet impact angle, but at the sacrifice of material removal rate. Predictive models for material removal rate and micro-channel depth are then developed using a combination of the dimensional analysis method and the particle impact erosion theories, where the squeeze film effect on the impact erosion is considered. The models are verified experimentally and it is found that the model predictions are in good agreement with the corresponding experimental data.
In this article, large direct current is applied through the tool to improve formability while forming 6061-T6 Al using single-point incremental forming. Special attention is paid to the direct effect of current density, as opposed to bulk resistive heating, to determine whether the electroplastic effect is significant in raising the formability without requiring temperature rise. Tests are performed to determine the maximum wall angle that can be formed for a variety of current and tool settings. The area of contact between the tool and sheet is modeled, and a control system is proposed and tested to vary the current to maintain a constant current density during tests. The phenomenon of current threshold density is observed at a current density range agreeing with previous studies forming the same material in different loading cases. A significant formability increase is observed at a range of current density values that agree with previously published work with this material in different loading cases. Surface roughness and spalling are also shown to be directly affected by current.
This article presents the results of simulated hemispherical die stretching of low-carbon steel (ST12 and ST14) blanks of various thicknesses. The simulations were designed to obtain forming limit diagrams. Multiple criteria, including the second time derivatives of major strain, thickness strain and equivalent plastic strain extracted from the strain history of simulations, were used to accurately detect the start of necking in forming limit diagrams. This is to say that necking starts when the second derivative of the thickness strain, major strain or plastic strain reaches its maximum value. Knowing the onset of necking, one can measure the major and minor strains at the critical area and produce the corresponding forming limit diagram. Moreover, a modified Marciniak and Kuczynski method was used to predict the forming limit diagrams. The results from the proposed methods and those from experimental tests are compared to demonstrate the efficiency of the proposed methods.
Designing parts with freeform surfaces, as typically applied in dies and moulds, is currently dealt with through designer experience, if design intent is to be maintained and if, at the same time, the manufacturing process is to be facilitated. This work puts forward a solution to these issues which is based on computational intelligence. A library of freeform surface morphological features is defined using parametric wireframe models that include constraints. The part is constructed using wireframe features from this library and these are subsequently converted to solid models. The effect of changes of feature parameter values is linked to part functional characteristics in standard design environment. Regarding the effect on manufacturing process characteristics, various models may be employed. As an example, a fuzzy system that decides tool diameter and the necessity of a semi-finishing operation is employed in this work. Artificial neural networks are trained with a number of workpiece variations corresponding to different feature parameter values and the pertinent outputs from functional and manufacturing assessment. Next, a standard genetic algorithm is set up to find the best values of the feature parameters based on both functionality and manufacturing criteria with suitable weighing. The evaluation function of the genetic algorithm employs the artificial neural networks constructed as metamodels. The methodology is demonstrated through an illustrative case study, but may encompass further Design-for-X disciplines.
With the enhancement of people’s environmental awareness, low-carbon and energy efficiency in manufacturing industry have been drawing much attention due to the huge consumption of raw materials and energy during machining processes. But as one of the approaches to reduce carbon emission, manufacturing shop scheduling strategies have historically emphasized the makespan, machine workload, and so on and neglected energy and environmental factors in most cases. This article presents a model of low-carbon scheduling of the flexible job shop, which considers both factors of production (i.e. makespan and machine workload) and environmental influence (i.e. carbon emission). A carbon footprint model of multi-job processing is established to quantify the carbon emission of different scheduling plans, and three carbon efficiency indicators are put forward to estimate the carbon emission of parts and machine tools, that is, processing carbon efficiency, part carbon efficiency, and machine tool carbon efficiency. To solve the proposed model, a hybrid non-dominated sorting genetic algorithm II which combines the original non-dominated sorting genetic algorithm II with a local search algorithm based on neighborhood search is proposed. Finally, test of some well-known benchmark instances is carried out to verify the effectiveness of the proposed algorithm, and an actual case is studied to demonstrate the feasibility and applicability of the proposed model.
Composite/metal stacks are widely used in aerospace structures. To study the mechanism of damage generation during drilling of carbon/epoxy composites and titanium alloy stacks, both traditional drilling and orbital drilling were used. Because the cutting parameters of the two drilling processes were different from each other, an appropriate comparing method was proposed based on the analysis of kinematics of orbital drilling and traditional drilling. The results show that high cutting temperature is the main reason for the damage generation during drilling of composite/titanium stacks. Cutting heat generated during machining of titanium alloy conducts to the composites and leads to the increase of composite temperature. High cutting temperature induces the degradation of carbon/epoxy composite properties, which results in the generation of damage during machining of composites. The cutting force in axial direction during orbital drilling is generally as high as that during traditional drilling. However, the temperature during orbital drilling is 36.3% less than that during traditional drilling. High cutting temperature and continuous chip generated during traditional drilling cause the high hole-wall roughness of titanium alloy. The lower temperature during orbital drilling is responsible for the machining quality of orbital drilling being higher than that of traditional drilling.
Polymeric materials have been widely used to replace traditional metallic materials due to their high specific elastic properties. Even though polymeric materials can be produced as near net shapes, machining is still required to make the assembling of the final products. The selection of tool and cutting conditions is very important to machine plastics because of the high ductility and low melting point of the materials. In this study, the machining behaviour of high-performance engineering polymers, such as ultra-high-molecular-weight polyethylene, polyoxymethylene and polytetrafluoroethylene, has been investigated using a full-factorial design (design of experiment). The effect of the factors such as feed speed, spindle speed and drill point angle was identified for each of the response variables (circularity error, surface roughness (Ra) and thrust force (Ff)). The drilling mechanism was substantially affected by the physical and mechanical properties of the polymers. Different cutting set-up conditions were able to optimize the responses. The polytetrafluoroethylene exhibited better results, achieving lower circularity error, surface roughness and thrust force. In the opposite manner, the ultra-high-molecular-weight polyethylene exhibited a rough topography at low feed rate and spindle speed levels.
Thermal error is one of the major sources of machining inaccuracy. It becomes the dominant source of error and therefore should be predicted and compensated for. This article proposes a vector-angle-cosine hybrid model for thermal error prediction. The model combines the advantages of different constituent models and makes full use of the original measurement results. A multivariable linear regression model, a natural exponential model, and the finite element method are chosen as the three constituent models, and their advantages and disadvantages are demonstrated in detail. The combination weights of the three constituent models are determined by maximizing the cosine value of the angle between the vector-angle-cosine prediction vector and the actual thermal error vector. Experiments on spindle thermal errors are conducted to build and validate the proposed model. The performance comparison between the vector-angle-cosine hybrid model and the three constituent models indicates that the former has better accuracy and robustness under different working conditions. Some actual machining tests are conducted pre- and post compensation, and results show that the size errors are decreased by 60%.
This investigation was focused on the high-speed laser welding of 0.4-mm tin-plated steels used for joining together parts of three-piece food cans. The high-speed laser welding quality is generally restricted due to several welding discontinuities that occur with the change of traverse speed. A study on the production set-up by a food can manufacturer was first addressed, and reasons for introducing high-speed laser welding were further discussed. A rotary axis as a welding fixture was designed and made to achieve high surface speeds. Thereafter, an experimental investigation was conducted using a CO2, neodymium-doped yttrium aluminium garnet laser and hybrid of plasma augmented laser welding applied to the typical food can material. Conventional welding defects found during high-speed laser welding were observed for all three laser welding techniques. However, humping gradients reduced with plasma augmented laser welding and penetration were evident up to welding speeds of 98 m/min. Furthermore, the high-speed laser welding defects were discussed, and possible solutions to eliminate the humps and further work into the application of the high-speed laser welding process for the Canning industry were mentioned.
Almost all machining industries in Sri Lanka use mineral oil–based and synthetic oils as metal working fluids during machining. But their usage has potential for long-term environmental pollution and threat to workers’ health. Therefore, much effort has been focused on research and development of eco-friendly and hazard-free alternatives to mineral oil–based metal working fluids, and the use of vegetable oils is one such alternative. This study was focused on investigating the easy access of vegetable oils in Sri Lanka and most commonly machined metals in the local industry, so that the outcome would be much more beneficial to the local industries. After several tests with 10 candidate vegetable oils, white coconut oil is selected as base oil and the results of a successful questionnaire survey directed to select mild steel and AISI 304 steel as the machining metals. Machining experiments were planned using Taguchi methods, and the variation of the surface roughness was tracked with respect to four variable parameters depth of cut, feed rate, spindle speed and metal working fluid. Two mathematical models were developed to predict the surface roughness and optimize the parameters. Further experiments were conducted to investigate the effects of metal working fluid for smooth- and rough-cut conditions. These experiments revealed that white coconut oil is a better metal working fluid for mild steel, while soluble oil favors AISI 304 steel. Different thermal conductivities of metals cause the coconut oil to act differently while machining two metal types.
In this study, a simple two-dimensional measurement system based on optical design was developed to measure the motion errors of the linear guideway. Compared with the transitional methods about the linear guideway for measuring the motion errors, our proposed two-dimensional optical measurement system can simultaneously measure horizontal and vertical running straightness errors for the linear guideway. Calibration results showed that the residual error of the two-dimensional optical measurement system is less than 0.5 µm. Measurement results showed that the three tests for the motion errors of the linear guideway are almost coincident with the laser interferometer within 1000 mm. The standard deviations of the horizontal and vertical straightness measurement systems are 0.9 and 1.2 µm.
Elastic–plastic finite element analyses were carried out to sort out the influential factors on the dimensional precision of cold-drawn stainless steel seamless tube for energy industry. Good agreement was obtained between the predicted dimensions and the measured dimensions of tube after drawing experiment for validity check. Geometrical parameters of tools and geometry of parent tube have little influence on the geometrical precision of finished tube. Most influential factor on the geometrical precision of drawn tube is the temperature of tools. Observation and measurement on a production line showed that the temperature of tools increases according to the increase in the number of drawn tubes. Increase in the temperature of tool leads to the change in the geometry of drawn tube. A methodology for evaluating the thermal expansion of tools is shown to take it into consideration the designing procedure of cold-drawing process by using finite element analysis.
In this study, the effects of the main process parameters involved in CO2 laser cutting of 1.5-mm twinning-induced plasticity steel sheets have been investigated by means of experimental tests. The quality of the cut edges of the sheets was evaluated by analyzing the kerf width, kerf deviation, roughness of the cut surfaces, and dross attachment. The process parameters used were the laser power, cutting speed, oxygen pressure, and pulse frequency of the CO2 laser beam. The optimal settings of the process parameters were predicted using the Taguchi parameter design approach with an L27(313) orthogonal array and calculating the average effect of both the laser parameters and the signal-to-noise ratios. Analysis of variance was performed to evaluate the statistical significance and the contribution of the laser process parameters to the examined kerf features and roughness. On the basis of the Taguchi approach, the predicted optimal settings of the process parameters were verified through confirmation tests. The results show that the selected process parameters, as well as their interactions, can have a remarkable effect on the cutting quality of twinning-induced plasticity steel sheets. The laser power is the main process parameter that affects the kerf width on both sheet sides, while the pulse frequency and its interaction with the laser power are the main factors that influence the kerf deviation, followed by the cutting speed. The roughness of the cut surfaces is mainly affected by the oxygen pressure and the interaction between laser power and cutting speed. Dross attachment was primarily observed in the specimens cut with high laser power and low cutting speed.
TC21 alloy is a new alpha–beta damage tolerance titanium alloy with high strength and high toughness. Little work has been done in the field of machinability analysis since this alloy was developed. The cutting forces and tool wear in high-speed milling of TC21 alloy with physical vapor deposition ((Ti, Al)N-TiN)-coated carbide tools under different cutting conditions were investigated in this article. The results showed that the cutting force component F x was more dominant of the three components, and the cutting forces presented an increasing trend with the tool wear progress, which in turn deteriorated the cutting condition and accelerated the tool failure progress. The major tool wear modes in high-speed side-milling TC21 alloy with coated carbide were adhesion and chipping on the rake face along with chipping and transverse crack on the flank face. Moreover, there was obvious nose depression from both the rake face and the flank face. Chipping along the flank and rake faces was identified as the main factor responsible for the failure of the coated carbide tools during the milling of titanium alloy TC21.
When controlling friction stir welding, effort must be given to maintaining proper tool shoulder contact with the workpiece in order to achieve consolidation of the parent materials. Axial force control has been used prior with some success. The research presented in this article examines the controlling of welding torque as an alternative to force control. A mathematical model of welding torque was enhanced for the design and study of convex shoulder profiles. Focus was placed on linearizing the response between plunge depth and torque. The model predicted that a spherical profiled shoulder was preferred for a more linear response. In conjunction with the spherical shoulder, a closed-loop torque controller was implemented and its performance evaluated. Welding torque for feedback control was sensed indirectly through the spindle motor current using a commercially available clamp-on current meter. The system produced 1/4 in (6 mm) bead-on-plate welds that were 10 ft (3 m) in length. Over the course of the welds, the torque controller responded to workpiece elevation changes of 1/8 in (3 mm) and 1/4 in (6 mm). Results show that the tool maintained a near constant plunge depth into the workpiece as the tool traversed along the workpiece. It was concluded that the presented method of torque control is a reliable and less complex alternative to axial force control of friction stir welding.
The residual stress within a surface layer of aluminium alloy sheets introduced through equal channel angular rolling as a severe plastic deformation process is studied in this article. The channel oblique angle, the route of feeding and the number of passes are the main equal channel angular rolling parameters that are found to influence the residual stress magnitude and distribution. Two aluminium alloys (Al5083 and Al6061) are analysed with the residual stress magnitudes determined using the X-ray diffraction method. When a sheet metal is processed using the equal channel angular rolling method, the surface residual stress in the rolling direction becomes compressive at the top surface and tensile at the bottom surface. Therefore, a nonuniform stress distribution is introduced into the specimen. By reducing the channel oblique angle of the die set from 130° to 110°, the surface residual stress of Al5083 specimens decreased by a maximum value of up to 27%. Combined with this, the surface residual stress decreases as the number of passes increases from one to three passes. These values depend on the route of passing the specimen through the dies during the equal channel angular rolling process. In addition, for materials with different inherent mechanical properties, the introduced residual stress is found to vary. The results indicate that the magnitude of surface residual stress for the Al5083 specimens processed by equal channel angular rolling is about two and a half times greater than the Al6061 specimens. The equal channel angular rolling process and its parameters had a similar effect on both Al5083 and Al6061 specimens. Therefore, the obtained result can be applied for sheet and strip metals.
Ball-end milling cutter with tooth offset center is widely used in machining industry, because it has higher machining efficiency and better stability compared with the ball-end milling cutter without tooth offset center. In addition, the tooth offset center has lower wear rate of the tool tip so the life of the milling cutter is improved. However, up to present, there is no mature and effective theory for the design and manufacture of this kind of milling cutters. This article presents a new mathematical model for S-shaped edge curve of the ball end taking the tooth offset center into account, which can construct accurate S-shaped edge curve for the ball-end cutting tools with tooth offset center as well as without tooth offset center. This model overcomes the complex computation and bad adaptability of the traditional modeling method. At the same time, a five-axis grinding algorithm for rake face of the ball end is also presented in this article. Finally, based on the application programming interface of CATIA™, a three-dimensional computer-aided design and computer-aided manufacturing system is developed. The accuracy and effectiveness of the grinding algorithm are verified by simulation in VERICUT™ and machining experiment in tool grinding machine.
Fixture error is one of the error sources in machining operations. Locator position inaccuracy and locator height error are the main sources of fixture error. The optimal positions of the locators are a critical problem for minimizing the geometrical and dimensional error of workpiece. This article proposes a genetic algorithm–based optimization method to arrive at a layout of locators for minimum machining error in 3-2-1 locating approach. The focus of this optimization is the positional tolerance of holes. So, a mathematical model of the hole position tolerance with respect to variation of locator position is developed. The planes of the workpiece actual coordinate system are mathematically modeled on the workpiece theoretical coordinate system. The capability of the proposed approach has been shown by using an example. The result shows that the proposed genetic algorithm method can be used to calculate locating errors and find the optimal locating layout within the specified tolerance range, which is critical for fixture design in hole-making process.
In this article, a novel redundant 3-degree-of-freedom parallel kinematic mechanism with high rotational capability is proposed and alternate configurations are presented. Taking the motion/force transmissibility into consideration, a local minimized transmission index is introduced and suggested to act as the performance evaluation criterion for this redundantly actuated parallel kinematic mechanism. On this basis, the optimum design of the proposed parallel kinematic mechanism is carried out and its rotational capability is investigated. The result indicates that the rotational capability of the proposed mechanism can surpass 115°. Compared with traditional parallel kinematic mechanisms, this represents a substantial advantage for practical applications. Using the redundant parallel kinematic mechanism as the parallel module, a redundant hybrid machine tool capable of five-face machining in one setup is developed and applied in the manufacture of parts with freeform surfaces.
This study implemented an iterative experimental approach in order to determine the shielding gas flow required to produce high-quality welds in the gas metal arc welding process with alternating shielding gases when subjected to varying velocities of cross drafts, thus determining the transitional zone where the weld quality deteriorates as a function of cross-draft velocity. An artificial neural network was developed using the experimental data that would predict the weld quality based primarily on shielding gas composition, alternating frequency and flow rate and cross-draft velocity, but also incorporated other important input parameters, including voltage and current. A series of weld trials were conducted to validate and test the robustness of the model generated. It was found that the alternating shielding gas process does not provide the same level of resistance to the adverse effects of cross drafts as a conventional argon/carbon dioxide mixture. The use of such a prediction tool is of benefit to industry in that it allows the adoption of a more efficient shielding gas flow rate, while removing the uncertainty of the resultant weld quality.
In this article, we have explored multi-item capacitated lot-sizing problem by addressing the backlogging and associated high penalty costs incurred. At the same time, penalty cost for exceeding the resource capacity has also been taken into account. Penalty cost related to both backlogging and overutilizing capacity has been included in main objective function. The main objective is to achieve such a solution that minimizes the total cost. The ingredients of total cost are the setup cost, production cost, inventory holding cost and aforementioned both the penalty costs. To solve this computationally complex problem, a less explored algorithm "biased random key genetic algorithm" has been applied. To the best of our knowledge, this research presents the first application of biased random key genetic algorithm to a lot-sizing problem. To test the effectiveness of proposed algorithm, extensive computational tests are conducted. The encouraging results show that the proposed algorithm is an efficient tool to tackle such complex problems. A comparative study with other existing heuristics shows the supremacy of proposed algorithm in terms of quality of the solution, number of generation and computational time.
In this study, a rheology vacuum low-pressure die caster is developed by installing a vacuum system in the die and an electromagnetic stirrer in the rasing pipe of a low-pressure die casting system. The cavity dimensions are 130 mm in the filling direction and 110 mm in the vertical direction, with a thickness of 1 mm. The fluidity of the material inside the die cavity is improved by maintaining the vacuum state inside the die. The electromagnetic stirrer is attached to the outside of the rasing pipe, which connects the furnace to the lower die. The application of the electromagnetic stirrer enables the achievement of microstructure with fine and globular primary α-Al particles by disrupting the dendrite structure. A mild filling simulation is conducted using a commercial casting analysis program prior to an experiment with the rheology vacuum low-pressure die caster. The rheological behaviour of the material inside the die is observed. A rheological thin plate is fabricated by applying a melt temperature of 615 °C, a vacuum of 60 Torr, and a gas pressure of 15 bar. There is little eutectic structure, with primary aluminium grains of 30 µm or below that are mostly distributed due to the effects of stirring. The tensile strength and elongation are 120 MPa and 15%, respectively. The hardness is 61–66 HV.
This article focuses on comparing the performance of brass wire and zinc-coated brass wire that are widely used as the wire electrode in wire electrical discharge machining. To this end, an evolutionary computation method is presented based on non-dominated sorting genetic algorithm in order to find an optimization of rough cutting of the Ti-6Al-4V titanium alloy with the aid of response surface methodology modeling. This research examines the effects of three process parameters, namely, pulse on-time, pulse off-time, and peak current on the process outputs, that is, material removal rate, sparking gap, and white layer thickness. The obtained results indicated that zinc-coated wire was more predictable and it showed more reliable response in the experimental and modeling results. Additionally, the optimization results for both wires demonstrated the high performance of non-dominated sorting genetic algorithm approach to obtain the Pareto optimal set of solutions.
Tube hydroforming with radial crushing is a new tube hydroforming process to manufacture very long components with complex cross sections. A loading path is generally considered a major factor that greatly affects the formability of a component by tube hydroforming. In this study, the tube hydroforming with radial crushing process of a square cross-sectional component was investigated by using the finite element method, and a method to predict the optimal loading path for the tube hydroforming with radial crushing process was developed from the finite element simulation. A multi-object function was first built in terms of the die-filling ability, cross-sectional symmetry, and wall thickness uniformity. Subsequently, a multi-strategy approach, characterized by a genetic algorithm and the bisection method, was developed to predict the optimal loading path. The effectiveness of the prediction method was verified by comparing the formability of components deformed under the optimal and conventional loading paths. Furthermore, the developed multi-strategy approach was demonstrated to have high efficiency when the total calculation times for the multi-strategy approach and for genetic algorithm alone were compared.
Product configuration is the key to mass customization, which is based on configuration modeling and solutions. A customer-oriented optimal configuration model is built to achieve an optimal configuration for a product scheme. Based on a product platform and customer requirements, a dual-objective "performance-cost" optimization model for customized products is proposed. This model is based on the Pareto genetic algorithm for configuration optimization through which optimal solutions for customer requirements can be obtained, including multiple choices for selection as well as reference to schemes that can enable customers to participate in the product design. In this study, a case is studied to prove the feasibility and effectiveness of the proposed model.
In self-propelled rotary tool machining, a circular cutting tool insert is used that continuously rotates about its axis during machining, as the tool is fed into the workpiece. The continuous rotation of the insert allows the insert to cool between engagements and improves tool life. In order to make use of this methodology for rough machining and bulk material removal in machining of aerospace materials, a self-propelled rotary face milling cutter is developed at Defence Research and Development Laboratory, Hyderabad. This cutter was developed to study the influence of inclination angle on the cutting forces generated during machining, and hence the cutter is provided with the provision to have the inclination angle of the insert for 20°, 30°, 40° and 50°. This article discusses the performance of the developed self-propelled rotary face milling cutter in face milling of titanium alloy at different inclination angles. The cutting forces developed in FX, FY and FZ directions are evaluated at different cutting speed, feed, depth of cut and inclination angles. The cutting forces obtained in self-propelled rotary face milling cutter is compared with that of conventional face milling cutter and the results are presented and discussed. Finally, regression models for prediction of cutting forces are developed.
There is a growing need to perform automated visual surface inspection in various manufacturing processes due to increased emphasis on quality control. A number of high-resolution three-dimensional metrology products are commercially available, but they are all very limited in their fields of view. The small field of view of the scanners makes inspection of relatively large parts a time-consuming operation, which has significant negative impacts on throughput. This article presents a two-stage inspection process in which a machine vision system, based on the photometric stereo principle, is used to detect potentially defective regions on parts over a much wider field of view than the one covered by the commercial products. The suspicious regions are then inspected using a high-resolution commercial three-dimensional surface measurement system, ignoring areas that are perceived to be defect free. Experimental tests on planar steel samples, having known surface defects, show that this approach is effective and it reduces the overall inspection time significantly.
Mechanical and microstructural properties of titanium alloys change with β-phase fraction. This in turn influences the dominant tool wear mechanisms in their machining. This work therefore involves turning experimentation on three titanium alloys with varying β-phase fraction, namely, α, α+β and β-rich alloys using coated carbide tools, to identify dominant wear mechanisms, which hitherto have not been adequately investigated. The dominant wear mechanisms were investigated using scanning electron microscopy and energy-dispersive X-ray analysis of worn tool surfaces and were also correlated with the cutting forces during machining. Abrasion, abrasion with built-up edge and plastic deformation of cutting edge appeared to be the dominant tool wear mechanisms in α, α+β and β-rich alloy, respectively. At the same time, diffusion of Sn, V and Mo from α, α+β and β-rich alloys to tool face, respectively, was observed. The chip–tool contact length predicted using the analytical models from the literature matched closely with the experimental values.
In this study, the surface modification and metallurgical analysis of three commonly used die steels were analyzed by microstructure and X-ray diffraction analysis after electric discharge machining and powder-mixed electric discharge machining. The effect of many process parameters was assessed for surface modification using magnetic field–assisted electric discharge machining process. It was observed that the microhardness of the machined surface increased by more than 200%. The analysis of machined surface confirmed material migration from added powder, dielectric and electrode. The magnetic field assisted in improving the material removal process. The strength of the magnetic field resulted in better expelling of material from workpiece and restricted the material migration from electrode especially in copper-based diamagnetic material. Deposition of tungsten and titanium carbide was observed, which increased the microhardness significantly. Titanium, tungsten and graphite powder aided favorably the increase in the microhardness.
In this study, a hybrid composite material was fabricated by stacking carbon fiber–reinforced plastic on CR340 plates to increase the specific strength and specific stiffness, compared to thick boron steel plates or dual-phase steels. A deep drawing test was conducted for this hybrid composite material, using various process parameters, to assess its formability and potential use in vehicle parts. The experimental results showed that the forming depth was reduced in both CR340 and the CR340/carbon fiber–reinforced plastic composite when the blank holding force (Bf) was increased. Although the forming depth of CR340 was decreased abruptly when Bf >= 30 kN, the forming depth of the CR340/carbon fiber–reinforced plastic composite was not reduced, highlighting its superior formability compared to CR340. The forming depth for CR340 did not show significant differences with increasing punch velocity. On the other hand, the forming depth of the CR340/carbon fiber–reinforced plastic composite decreased with increasing punch velocity. As the punch velocity increased, carbon fiber–reinforced plastic flowed abruptly toward the round part of the die. The thinning rate in each position of the drawing product and the problems encountered during the deep drawing process were reviewed by a comparison of the experimental results.
In this study, a hydroforming process is used for the manufacture of a bicycle frame tube, one side end of which is expanded to an acute-angled triangular shape from the initial tube, which has a regular triangular cross section. The end section of the expanding side is designed to be smoothly connected with the initial tube cross section to maintain sealing by the plunger. The tube hydroforming process is controlled using an axial feeding plunger and a pressure intensifier. Various load conditions can be applied to the initial tubes through these units. However, the experimental results showed that forming into the desired shape without bursting at the expanding area or shear cracking at other areas was not possible. These problems seem to occur because the circumferential propagation of plastic deformation is constrained by the triangular cross-sectional profile of the initial tube. To resolve this problem, less axial feeding should be supplied to the compressing zone compared with the expanding zone even in a single tube. In this work, besides conventional axial feeding, an additional axial feeding method by an end cam–shaped plunger is suggested to supply different axial feeding for each circumferential location of the tube. Finite element simulation and experimental studies are performed to verify the effectiveness of the concept.
Thanks to its superior mechanical and physical properties, silicon carbide is a promising mold material in glass molding of micro-structured optical elements. However, the high micro-structured surface quality can be hardly generated by means of conventional abrasive polishing because of the high hardness of silicon carbide. In this article, the ultrasonic vibration was introduced to assist abrasive polishing with an aim to improve the cylindrical groove arrays’ surface quality and also to increase the polishing efficiency. First, the comparison experiments between abrasive polishing and ultrasonic vibration–assisted polishing were conducted, and then, the factors affecting ultrasonic vibration–assisted polishing performance were investigated. The experimental results indicate that through conventional abrasive polishing, the surface roughness of silicon carbide cylindrical groove arrays decreases to 25.5 nm from the precision ground surface roughness (Ra) of 115.6 nm, while through ultrasonic vibration–assisted polishing, the surface roughness decreases to 8.6 nm with a factor of three times improvement. Furthermore, a 35-kHz vibration frequency corresponds to a smaller surface roughness than a 25-kHz vibration frequency under identical processing parameters. In the vibration amplitude range from 1.0 to 2.5 µm, the surface roughness accordingly decreases linearly, while in the range of 2.5–4.0 µm, ultrasonic vibration presents no assistance in improving the surface quality.
Extrusion–shearing of magnesium billets is associated with large deformations, high strain rates and high temperatures, which could result in many difficulties in process. Thermo-mechanically coupled three-dimensional finite element simulations of extrusion–shearing wrought magnesium alloy AZ31 into small rods at certain speed have been performed, and computed parameters including workpiece material characteristics and process conditions (billet preheated temperature, extrusion ratio, ram speed, friction factors and heat transfer coefficients) have been taken into consideration. The temperatures and stress and strain rates of extrudates with different billet preheated temperature have been calculated by finite element method software DEFORM-3D. A series of extrusion–shearing experiments and microstructure observations have been done to perform tests in order to validate the finite element method simulation results at different preheated temperatures of billets. Surface defects of rods for magnesium alloys extruded by the extrusion–shearing extrusion have been observed and analyzed. The influences of preheated temperature on the microstructures and the causes have been given. Finite element method software DEFORM-3D has been used successfully to simulate the temperatures and stress and strain rates under three different extrusion conditions. The results of these simulations helped to understand the formation of surface defects in the surface of extrusion–shearing rods. These results could assist in improving quality of extrusion–shearing extrusion.
A new development of equal channel angular pressing method to fabricate wire-formed samples has been proposed and experimented. In this approach, wire-formed specimen, which is inserted inside a polyurethane rubber pad material, has been pressed using conventional equal channel angular pressing die. Commercial pure copper samples in the shape of wire have been equal channel angular pressed up to 12 passes by route BC, and then hardness behavior, electrical conductivity and microstructure observation of deformed samples have been examined. The results indicate that about 77% and 66% enhancements at the hardness value (HV) magnitudes have been obtained after 8th and 12th passes, respectively, as compared to the unequal channel angular pressed state. Reductions of about 92% and 95% at the grain size of pure copper have been observed after 8th and 12th passes, respectively, in comparison with the annealed condition. Also, the first pass of equal channel angular pressed wire has both the worst hardness distribution homogeneity and the lowest electrical resistivity. On the other hand, the final pass of pressed wire has both the best hardness dispersal uniformity and the highest electrical resistivity.
This research study investigates the suitability of micro-computed tomography as a non-destructive technique to assess the morphology of nylon 12 parts manufactured using laser sintering. Density measurements and morphological and mechanical characterisations were performed on sintered nylon 12 parts to measure density and morphological and mechanical properties of the parts. The effects of various levels of laser power on the density, morphological parameters and mechanical properties were investigated and compared. The results show that micro-computed tomography can be used to measure the porosity and pore size of the sintered parts. Micro-computed tomography images provide an understanding of the changes in the three-dimensional structure of the parts. There is no evident change in the porosity or pore size of the laser sintered parts with the increase in laser power. The results of the tensile tests show that the changes applied in laser power had no apparent effect on the ultimate tensile strength and Young’s modulus of the laser sintered parts. However, the elongation at break for the parts generally increases as the level of laser power increases. A relationship between non-destructive micro-computed tomography and destructive tensile test results is shown.
Surface roughness is an important parameter that determines the post-manufacturing product quality. In this study, effect of cutting parameters, coating material and the built-up edge phenomenon on the surface roughness were investigated in micro end milling process of Inconel 718 using a white light interferometer and scanning electron microscopy. A micro end mill with a diameter of 768 µm coated with five separate coating materials (AlTiN, AlCrN, TiAlN + AlCrN, TiAlN + WC/C and diamond-like carbon) was used in this study. According to the results obtained, mean surface roughness values of surfaces machined with a diamond-like carbon-coated and AlTiN-coated cutting tool were lower than for other coatings. However, surface roughness values of surfaces obtained with tools coated with TiAlN + AlCrN and AlCrN were higher. Specifically, the formation of built-up edge causes chips to be smeared on machined surfaces, which has a negative impact on the surface quality. As can be expected, wear occurs faster on uncoated tools. As a result of this, the edge radius may increase excessively, and the mean surface roughness value may decrease. Also in this study, multivariate analysis of variance was carried out and the parameter that was most effective on surface roughness was established.
Three-dimensional model–based virtual assembly process planning plays an important role in assembly design of complex product and is typically time- and resource-intensive. There are limited effective solution frameworks for delivering the three-dimensional model–based assembly process information to assembly field in order to directly guide the assembly tasks on site. A cloud service architecture for mobile three-dimensional model is proposed to address these challenges. Under this cloud computing architecture, this article introduces a dynamic assembly simplification approach, which regards the virtual assembly process of complex product as an incremental growth process of dynamic assembly. During the growth process, the current-assembled-state assembly model is simplified with appearance preserved by detecting and removing its invisible features, and the to-be-assembled components are simplified with assembly features preserved using conjugated subgraphs matching method based on MapReduce. The proposed approach has been tested on several cases, and the results show its feasibility and superiority.
In the modern global economy, the product-service system strategy is increasingly popular with manufacturers. However, to the best of our knowledge, the publication focusing on the supply chain model for product-service system is still scant. Based on the findings of a half-year investigation in an air compressor manufacturer in China, the article is trying to develop a comprehensive framework of supply chain for product-service system. By exploring the structure and the unique features of the supply chain for product-service system, the research leads to a better understanding of the subject. Following the analysis, the supply chain model for product-service system is developed and elaborated in the value co-creation, functional process management, and the enabling process management. It is hoped that the exploration will form the frontier basis for further research on supply chain for product-service system.
The grinding experiment of mica glass-ceramics was conducted on the GM-D300-type surface grinder. The article investigated the influence of surface roughness on grinding wheel velocity, table feed speed, and grinding depth. The results indicated that surface roughness decreased with the increasing grinding wheel velocity and grinding depth in overall trend, and decreased with increasing table feed speed. Moreover, a modified surface roughness model, which introduced the maximum undeformed chip thickness, was developed based on Snoeys’ empirical formula. The modified model was in good agreement with the experimental data in most cases. The disparity between experimental data and predicted results of surface roughness was attributed to the organization of pores randomly distributed within the mica glass-ceramics.
The fierce competition in the global manufacturing environment is forcing enterprises to seek competitiveness beyond traditional aspects such as functions, quality, cost, and lead time. An emerging strategy is to develop sustainable manufacturing systems. An ideal sustainable system has the characteristics of remanufacturing, redesigning, recovering, reusing, recycling, and reducing. However, this type of sustainability mainly refers to the products rather than to the manufacturing system itself. When the design and operation of a manufacturing system are concerned, the criterion of sustainability often conflicts with other requirements such as cost and lead time. Instead of establishing a total new system paradigm, it is more realistic that the concept of sustainable manufacturing is used as a guidance to evolve existing systems to an advanced level. In this article, a case study is introduced to recycle an obsolete test machine to meet new functional requirements; it has shown a significant economic benefit. The presented case study provides a new perspective of economically evolving dedicated machines or manufacturing systems into sustainable systems.
The microstructure and mechanical properties of the deformed materials obtained by equal channel angular pressing are strongly dependent on the amount of induced strain and strain homogeneity developed during history of the process. In this work, a new route for equal channel angular pressing process was proposed and investigated by finite element method. This new route consists of a combination of Routes BC and C by alternating rotations through 90° and 180° after every pass. In other words, the billet is rotated 180° after the first and the third passes around its longitudinal axis like Route C and after the second pass is rotated 90° around its longitudinal axis like Route BC. In comparison with other routes, it was shown that the strain homogeneity achieved by this proposed route is better than other conventional routes. The finite element method results for Route BC were validated by available experimental data, which can support finite element method results for the new proposed route.
This work is a novel attempt to identify the optimum process parameters in cold upsetting of Al–TiC metal matrix composites with multiple responses using grey Taguchi approach. The formation of barrel and workability are the important attributes that greatly influence the process of upsetting. Three independently controllable process variables, namely, aspect ratio, friction factor and load, each at four levels are considered to find their optimum levels which yields maximum barrel radius and workability simultaneously. Grey Taguchi analysis has been performed to optimize the levels of input parameters. Both the quality characteristics are improved significantly at the optimal process condition as verified by the confirmation test. The effect of individual process variables on the responses is determined using analysis of variance.
This article investigates the impact of dielectrics on the properties of micro-holes fabricated by micro-electrical discharge machining. Based on experiments using kerosene and deionised water as the working fluid, the machining in different dielectrics is investigated. The flow of the water is analysed by means of a flow field simulation, and corresponding experiments are also conducted to verify the simulation results. Suitable parameters are obtained to process a micro-hole array with 256 holes, a configuration widely used in printer ejector mechanisms. The average diameter of the holes is 44.47 µm, and the maximum diameter deviation is 1.3 µm.
Advanced high-strength steels are being used widely in automotive industry to achieve lightweight construction and fuel efficiency. During advanced high-strength steel blanking, the die components have to sustain higher pressure, and this may result in some problems such as chipping, cracking, galling and severe die wear, which has a great effect on the die life. This study aims to investigate the wear resistance performances of five die materials (carburized 4Cr13, conventional SKD11, Caldie, A2 and tungsten steel D60) using a featured blanking die setup combining five different die materials. The surface topography and microstructure of punching die materials are measured by optical profilometer and microscope. Based on the measured results, the specified wear rate and worn profiles of die inserts are obtained and compared. It is demonstrated that Caldie and A2 have higher wear resistance performance than SKD11 and 4Cr13. Moreover, the experimental results display that the most severe wear locations occur at the interfaces of straight lines and circular arcs.
This article presents experimental studies on micromilling thin walls to explore process capabilities in direct manufacturing of high aspect ratio features using tungsten carbide micro-end milling tools for two different materials: aluminium and brass. This study has been conducted in two phases. At first, the effects of micromilling parameters on the surface roughness have been investigated and most suitable machining conditions in obtaining highest surface quality have been identified. In the second phase, the effects of machining strategies have been explored in order to optimize final quality of the thin walls in terms of straightness of the machined thin walls, uniformity of wall thickness and burr presence. As a result of this experimental study, optimized machining parameters and strategies are presented. In the case of micromilling brass (CuZn36Pb3), a down-milling cutting direction with a Z-step milling strategy at a spindle speed of 35,000 r min–1, an axial depth of cut of 150 µm and a feed rate of 150 mm min–1 provided the best overall thin-wall quality. In the case of micromilling aluminium (Al6061-T4), a down-milling cutting direction with a ramp milling strategy, a spindle speed of 25,000 r min–1, an axial depth of cut of 150 µm and a feed rate of 200 mm min–1 yielded the best results.
This article presents an integrated and systematic investigation into the interaction and effects of the abrasive flow machining factors, through its three major process variables of the media velocity, temperature and quantity, which play an essential role in interfacing the ‘machine’ with ‘workpiece’ and ‘media’ corners of the abrasive flow machining triangle. The article also presents predictive models, main effects and industrially useful rule-of-thumb tools. Collectively, these variables offer machine operators the ability to manipulate the process behaviour when the opportunity to modify geometry and media levels is unavailable. In the media and geometry corners of the triangle, capital expenditure is required to adjust levels, making them economically and temporally limiting. The machine adjustments are physically limited by the hardware in use; however, this research finds that the range of response magnitude can vary significantly among the three process outcomes studied, that is, surface roughness, material removal and peak height reduction. Using a standard media and testpiece set-up, data are collected using a 33 full factorial experiment design and translated into a response surface design (Box–Behnken) for predictive model development. Application to oil and gas industry parts is shown whereby data are utilised to aid in the abrasive flow machining of production parts.
The sheet metal hydroforming technique is easy to achieve lightweight and is widely applied in the aerospace and automotive fields. In order to realize the reliability test for uniaxial tensile forming properties of sheet metals under the condition of three-dimensional stress, experimental apparatus and dedicated fixtures for uniaxial tensile tests of sheet metals under fluid pressure are designed in this article. The stainless steel 304 is employed for this experiment, and commercial finite element software ABAQUS is also adopted to study the deformation behavior of sheet metals under fluid pressure. The results indicate that when the fluid pressure of gauge length reaches a certain value, the specific region will present "double necking" and the peak values of equivalent stress and reduction rate are much lower than that of the conventional ones. When the strain rate is 0.01 s–1, the elongation of the 0.95-mm thickness sheet increases more obviously, reaching 24.1%. With fluid pressure, the fracture morphologies of stainless steel thin sheets and thick sheets are all ridge distributed from both sides to the center of symmetry, and tiny dimples distribute mainly in the rest parts. Based on the results of the experiment and finite element method, the uniaxial tensile forming properties of sheet metals under fluid pressure have been evaluated successfully and easily by this experimental apparatus.
This article details experimental work performed to evaluate the effects of varying feed rate (0.08 and 0.15 mm/rev) and tool coatings (diamond-like carbon and chemical vapour–deposited diamond) on tool wear modes and hole quality when drilling 30-mm-thick Ti-6Al-4V/carbon fibre–reinforced plastic/Al-7050 stacks in a single-shot operation. At a feed rate of 0.08 mm/rev, the diametrical accuracy of holes produced by both the chemical vapour–deposited diamond and diamond-like carbon–coated drills (6.38 mm diameter) was comparable within a tolerance of ±0.04 mm even after 70 holes. However, in terms of cylindricity, holes machined with chemical vapour–deposited diamond were significantly better than those produced using the diamond-like carbon–coated drills by a factor of ~2 (65.7 vs 140.6 µm). A similar trend was also observed for hole out of roundness. Burr height at hole entry locations (Ti layer) ranged from ~0.03 to 0.08 mm for all trials undertaken at the lower feed rate level; however, the diamond-like carbon–coated drills generated exit burrs which were ~4 times larger than their chemical vapour–deposited diamond-coated counterparts. Subsequent wear analysis showed that diamond-like carbon–coated drills operating at 0.08 mm/rev typically exhibited progressive abrasion, workpiece adhesion and chipping leading to fracture of the tool corner, while fracture due to fatigue was prevalent in tests carried out at the high feed rate level. In contrast, poor adhesion of the chemical vapour–deposited diamond coating to the carbide substrate led to premature flaking, severe chipping and fracture of the drill cutting and chisel edge.
A successful tube hydroforming process depends largely on the loading paths for controlling the relationship between the internal pressure, axial feeding and the counter punch. The objective of this article is to propose an adaptive control algorithm to determine appropriate loading paths in T-shaped protrusion hydroforming with different outlet diameters. The finite element analysis is used to simulate the flow pattern of the tube during tube hydroforming process. The analytical flow line net configuration of the tube is utilized to determine the speed ratio of the counter punch to the axial feeding at the protrusion stage. Appropriate loading paths for different outlet diameters are determined using the proposed adaptive control algorithm. Different pressurization profiles are used in the tube hydroforming experiments. Experimental results show that a sound product is obtained using the pressurization profile determined by the proposed adaptive simulation algorithm. From the comparisons of the product shape and flow line net configurations between the analytical and experimental values, the validity of the proposed control algorithms is verified.
The low thermal conductivity and high chemical reactivity of titanium alloys result in a short tool life in the milling process. This article investigates the performance of polycrystalline diamond tools in the end milling of titanium alloys (Ti6Al4V) by using small customized cutting tools. The relationship between cutting force and cutting parameters was analysed; tool life, tool wear, and causes that lead to tool failure were discussed. To analyse tool wear and cutting temperatures, residual chemical components on the cutting tool were examined with X-ray diffraction method, while surface integrity of cutting tools was inspected based on the images taken by the scanning electrical microscope. Finite element analysis models were developed to simulate the initiation of cracks under different loading cycles. Through cutting experiments, it was found that brittle chipping and fatigue were the two major modes of failure, and feed rate was the dominant factor that causes large cutting forces.
Feature-based manufacturing methodologies offer opportunity for numerical control machining effectively and efficiently. However, the loss of drive geometries caused by the complex shape and machining process of aircraft structural parts undercuts the advantage of feature-based manufacturing tools. To better address the gap between the process planning and tool path generation for aircraft structural part, a drive geometry construction approach based on the topological relationships and machining process of machining features for process planning are proposed. The created drive geometries correspond with the optimized machining process. The drive geometries that define the machining areas of machining features are categorized into guide lines and guide faces in accord with the machining mode, such as 2.5- to 3-axis machining and multi-axis machining. In contrast to the traditional performing of intersection operations with a series of slice planes and the part model manually, the drive geometries are constructed by extracting the existing topological entities and creating some auxiliary topological entities automatically. The drive geometry preparing time and the consumption of computer memory are reduced significantly. The proposed approach has been tested and used in a pilot feature-based programming system that is developed for some aircraft manufacturers in China.
In the traditional manufacture methods of metal bellows, such as tube bulging and hydroforming, the dies and tools are generally used. In these methods, it is very inconvenient to change the shapes of bellows because the dies and tools should be changed, which often result in extremely high cost. In this study, a novel manufacture method without any dies and tools for producing the metal bellows with various shapes was proposed. This novel method is called as dieless bellows forming process with local heating technique. The factors which affect the shape of metal bellows and the deformation behavior of metal tubes during the dieless metal bellows forming process were investigated by experiment and finite element method simulation in this study. The metal tubes (SUS304, JIS) with the dimensions of 13.8 (D) x 2 (t) mm and 25 (D) x 2 (t) mm were used to study the availability of the newly proposed method for manufacturing the metal bellows with different tubular materials. As a result, the metal bellows with good shapes were successfully obtained using the newly proposed method. The results also showed that the shape of the metal bellows can be easily changed by adjusting the compression ratio. It was clarified that the deformation parameters, such as compression ratio and heating length, have the significant effects on the convolution height, pitch and deformation behavior of metal tube during dieless metal bellows forming process. The suitable parameters should be chosen to manufacture the metal bellows with the expected shape.
In ultrasonic-assisted wire electrical discharge turning, the longitudinal ultrasonic vibration of the wire creates a longitudinal compressive and rarefaction wave front, which is successively aiding very violent and accelerative mass to transfer across the spark gap, acting as a pump, causing higher debris suspension and evacuation from the gap and higher dielectric fluid renewal. For this purpose, a specially designed and fabricated turning spindle is used. An auxiliary device which produced the ultrasonic vibration was installed between the two wire guides. The ultrasonic system consists of an ultrasonic generator, a transducer, and a wire holder. When the wire is being driven, the transducer and the wire holder are vibrated under the resonance condition. In this study, the size of eroded craters, surface roughness, recast layer thickness, and micro-crack, measured on the workpiece (anode) were found to be highly influenced by the applied ultrasonic vibration. It was found that the volume of the eroded craters increased by applying the ultrasonic vibration based on single discharge analysis. This means that the remaining lower melting material leads to the reduction of the recast layer thickness and micro-cracks. Based on the obtained results, in this process, the surface roughness is not changed under low discharge energy (finishing condition).
In this study, a study has been conducted on fabrication and control of different grain sizes of micro features fabricated by ultrasonic-assisted jet electrodeposition process using pulsed current power supply. At the present time, grain sizes have been controlled to improve the mechanical properties of fabricated micro features. The centre of attention of the study is application of pulsed power supply on the developed ultrasonic-assisted jet electrodeposition set-up, which involves pulsed current application between nozzle (electrolyte) and work surface in ultrasonic-assisted jet electrodeposition process instead of direct current application. The impacts of frequency and duty cycle on the grain size, nanomechanical properties and microhardness of fabricated micro features have been studied. It is experimentally observed that the pulsed current ultrasonic-assisted jet electrodeposition process has the capability to fabricate nano-sized grain micro parts and yields better mechanical properties as compared to those obtainable using direct current ultrasonic-assisted jet electrodeposition process.
Aircraft assembly is the most important part of aircraft manufacturing. A large number of assembly fixtures must be used to ensure the assembly accuracy in the aircraft assembly process. Traditional fixed assembly fixture could not satisfy the change of the aircraft types, so the digital flexible assembly fixture was developed and was gradually applied in the aircraft assembly. Digital flexible assembly technology has also become one of the research directions in the field of aircraft manufacturing. The aircraft flexible assembly can be divided into three assembly stages that include component-level flexible assembly, large component-level flexible assembly, and large components alignment and joining. This article introduces the architecture of flexible assembly systems and the principles of three types of flexible assembly fixtures. The key technologies of the digital flexible assembly are also discussed. The digital metrology system provides the basis for the accurate digital flexible assembly. Aircraft flexible assembly systems mainly use laser tracking metrology systems and indoor Global Positioning System metrology systems. With the development of flexible assembly technology, the digital flexible assembly system will be widely used in current aircraft manufacturing.
Fixturing strategies during the different stages of manufacturing of a part strongly affect the final geometrical outcome on both part level and assembly level. Different manufacturing setups, processes and operations allow for, and put requirements on, the fixturing strategy. In this article, different fixturing strategies during cutting of stamped sheet metal parts are discussed and evaluated with respect to minimized variation in critical features. The strategies are discussed from a theoretical point of view. Geometrical decoupling philosophies are used to minimize the number of variation sources during cutting. The strategies are also illustrated using an industrial case study consisting of laser cutting of a stamped sheet metal part. Some general guidelines, based on the results, for fixturing during sequences of operations are formulated. In this article, fixturing during laser cutting followed by fixturing during assembly are in focus, but the strategies should be generalizable to other sequences of manufacturing operations as well.
Horizontal welding plays an important role in manufacture of large and heavy aluminium alloy structures. But there are many problems such as bad weld formation, porosity and low efficiency. Variable polarity plasma arc welding is a low-defect and high-efficiency welding technology, but it has difficulty in horizontal position. The maximum weldable thickness is less than 6.4 mm in single-pass weld. The soft plasma arc was proposed in this article. Horizontal welding of aluminium alloy plates with 8 mm thickness was realized successfully. The joint was free of defects and had excellent mechanical properties. This is a breakthrough in single-pass horizontal welding. Moreover, the characteristic of the soft plasma arc was studied in detail and the fluid flow in weld backside was observed. Finally, the forming mechanism of a stale weld pool was discussed. Results indicated that the arc pressure with the soft plasma arc was lower than that with the ordinary plasma arc. The fluid flow was asymmetric in horizontal position. The forming of a keyhole was realized by the bridging of the molten metals in the upper and lower sides. The weld pool was stable with the soft plasma arc because the maximum diameter of keyhole was bigger than that with the ordinary plasma arc.
This article reveals the influence of laser welding process parameter, welding speed, on the mechanical and metallurgical properties of 3.5 kW CO2 laser machine welded joints of 70/30 Cu-Ni alloys. Laser welded joints were fabricated using different welding speeds of 1.0, 1.5, 2.0, and 2.5 m/min. The mechanical properties (hardness, tensile strength, and percentage elongation) of the welded joints were evaluated and correlated with the fusion zone microstructure. Optical microscopy and scanning electron microscopy were used to evaluate the metallurgical characteristics of the welded joints. The joints fabricated using a welding speed of 1.5 m/min exhibited fine, equiaxed, and uniformly distributed grains at fusion zone and resulted in superior mechanical properties than other joints.
An aero-engine blade is the typical thin-walled workpiece with low rigidity. The machining accuracy of the aero-engine blade with sculptured surfaces has been a research focus in the aviation industry. This article presents a new cantilever grinding process for the high precision machining of aero-engine blade. Only one end of a blade is fixed and the other end is free in order to eliminate the deformation of blade caused by over-positioning. Moreover, the vibration of aero-engine blade can be reduced so that the surface quality of blade can be improved in the grinding. The grinding parameters are optimized for the low deflections of blade. The types of tool path are also discussed in this article. Finally, the computer numerical control machining examples are implemented. The measurement results show that the profile errors of suction/pressure surface machined by the proposed process do not exceed 0.02 mm. And the machining accuracy of leading/trailing edge with a radius of about 0.05 mm is acceptable.
The fabrication of nanostructure materials using severe plastic deformation techniques with improved properties has received attention over the recent years. Twist extrusion has become one of the most widely spread techniques of the severe plastic deformation processes. This article reports the experimental investigations on the twist extrusion forming of AA6082-T6 aluminum alloy. The central composite design was utilized to plan the experiments, and response surface methodology was employed for developing experimental models. The forming load, temperature and number of passes were considered as input parameters in this study. The process performances such as tensile strength and hardness were evaluated. The results of analysis of variance indicated that the proposed mathematical models obtained can effectively describe the performances within the limits of factors being studied. The experimental values were in good agreement with the predicted values.
This article proposes a method to find the optimized manufacturing procedure of ejector using differential evolution algorithm. To obtain the optimized machining conditions, the performance of ejector was analyzed based on the computer simulation, and machining condition during manufacturing was used to design the evaluation function. Based on the computer simulation and experiments results, the evaluation function for optimization and the manufacturing constraints were induced in this article. The functionality of the proposed method was verified through experiments.
Dual-chamber pneumatic spring vibration isolation tables are commonly used as the base of precision equipment to isolate vibrations from the floor. During the design of dual-chamber pneumatic spring vibration isolation table, transmissibility is often taken as the performance measure, which does not represent the precision requirements directly and could not be adapted to different floor vibration conditions. In this article, a new performance measure is developed to obtain an optimum isolation performance during the design of a dual-chamber pneumatic spring vibration isolation table. Based on the generic vibration criteria, the weighted root-mean-square velocity of platform vibration in one-third octave bands resulting from the floor excitations is used as the new measure. The platform vibration is predicted by establishing a model of dual-chamber pneumatic spring vibration isolation table, which consists of a platform and four dual-chamber pneumatic springs. The model disturbance inputs are actual random floor excitations (7.98 µm/s, vibration criteria-C level), which are obtained by vibration acquisition test in a typical laboratory. The genetic algorithm is applied to solve this nonlinear optimization problem. The maximum weighted root-mean-square velocity of platform with the optimum design isolation table decreases to 2.35 µm/s, which provides a vibration criteria-E level environment.
Clinching technology is widely used in the automobile and furniture industries. Shearing strength is an important criterion for evaluating the quality of clinched joints. Round and rectangular clinched joints are based on the shape of the tools. In this article, the shearing strength of round joints was designed and discussed. Two methods, namely heat treatment and press-join orientation, were presented. Different rolling directions for Al6061, Al5052, and Q235 sheets were connected to investigate the shearing strength of round joints at 90° and 180°. An electric furnace was used to heat the clinched joints of the Al6061 sheets to 430 °C, 450 °C, 530 °C, and 570 °C and obtain the optimal heat treatment temperature. Results proved that press-join orientation and solid-solution treatment affect shearing strength.
This article addresses scheduling problems for the hybrid cellular production lines in the semiconductor industry, in which the hybrid cellular production line is defined as the production system composed of both single-functional and multi-functional cellular layouts. Detailed system configuration and material flow of a hybrid cellular production line are presented, and then, the scheduling problems in the hybrid cellular production line are separated into an inter-cell scheduling problem and intra-cell scheduling problems. A multi-agent-based scheduling method is proposed for the inter-cell scheduling problem, and a real-time heuristic scheduling method is proposed for the intra-cell scheduling problem. In the simulation experiments, various scenarios have been compared under the proposed inter-cell and intra-cell scheduling methods with the hybrid cellular production line composed of six cells.
Ti-6Al-4V titanium alloy and 5A06 aluminum alloy were successfully butt-joined by friction-stir welding method utilizing a special design of butt-joint configuration. The tool-pin was bias placed toward the aluminum butt-side, accompanying with an excess plunge value of tool shoulder into the top surface of aluminum sheet. The as-welded interface characteristics, joining mechanisms and tensile properties of the modified titanium/aluminum dissimilar butt-joint were performed. Experimental results indicated that the defect-free butt-joints with good formation quality were obtainable when the rotation speed of 1200 r/min, the travel speed of 60 mm/min and the pin offset of 0.5 mm were tailored. The stir nugget zone in joints exhibited a composite-like structure of titanium-alloy particles distributed in aluminum-alloy matrix, with an obvious so-called onion-ring morphology. The energy-dispersive X-ray spectroscopy detections showed that no bulky intermetallic compounds were formed at the titanium/aluminum as-welded interface. The maximum tensile strength of the joint was 265 MPa, which generally reached 84.13% of that of the parent 5A06 aluminum alloy.
Although assembly line balancing problem has been an attractive field of research in many industries over the past decades, few researches focused on the problems in shipbuilding. In this contribution, we deal with a more realistic assembly line for sub-block in shipbuilding, through which lots of small different products were produced. Thus, the problem becomes more complex, which can be regarded as a variant of the classical assembly line balancing problem, batch-model assembly line balancing problem with space and sequence constraints. Our goal is to find the optimal division of the total assignment into different production batches based on the balance of the station workloads and higher efficiencies of the workers and equipments. We solve the said problem with a memetic algorithm, which is illustrated in detail. The validity of the proposed algorithms is tested using the real data of the sub-block assembly in shipbuilding, and the experiment results demonstrate that the proposed algorithm outperforms highly the existing standard genetic algorithm in terms of ability to find the optimal solutions.
Diamond-coated drawing dies are considered as the next generation of drawing dies for their unique characteristics, such as high hardness, wear resistance, low friction and thermal conductivity in the cold drawing process. In order to utilize the superior characteristics of diamond coatings toward improving the drawing performance, modified typed drawing die is developed to minimize the diameter shrinkage. Finite element model simulation is used to simulate the low carbon steel tube sinking drawing process, using a two-dimensional axi-symmetric elastic–plastic element model. The parameters of tube drawing die, such as the main reduction zone α 1, the semi-angle of the secondary reduction zone α 2 and the length of the secondary reduction zone L, are considered. Based on the simulation results, the cause of diameter shrinkage is studied. The influence of parameters of tube drawing dies on the diameter shrinkage is investigated using the response surface methodology. The gained equation reveals that L is the most significant parameter.
The rotary-draw bending process of thin-walled rectangular tube is a complex process with the interaction of many factors. The wrinkling may be produced if the process parameters are inappropriate. So, here, based on finite element numerical simulation, and taking the clearances and the frictions between tube and dies as the optimal design variables and the wrinkling height as the optimal objective, the optimization design for rotary-draw bending process of thin-walled rectangular 3A21 aluminum alloy tube has been carried out by using sequential quadratic programming method. Then, the recommended values of the clearances between mandrel, wiper die and bending die and tube, and the friction coefficients between pressure die, mandrel and wiper die and tube are obtained. The achievements of this study are significant to reduce the manufacturing cost and increase efficiency and bending quality.
The creation of textures and structures on contact surfaces is of importance for improving contact conditions for mating surfaces. Laser machining shows promise as a prospective technique in the fabrication of micro- and nanometre scale structures on difficult-to-cut materials. This study provides new information on manufacturing process operating variables for the use of femtosecond lasers in structuring the carbide tool rake face with a view to improving the tool–chip contact phenomena. Experiments were based on a femtosecond Ti:sapphire laser system with a wavelength of 800 nm, pulse duration of 100 fs and repetition rate of 1 kHz. The effect of laser fluence and scanning speeds on the geometry and quality of the structures was investigated. The research draws upon the requirements for cutting tools and defines the best laser process parameters to preserve the effectiveness of the carbide material in machining. This work is important for innovative development of cutting tools, alleviating critical contact conditions on the tool–chip flow faces and reducing energy demand in machining.
A novel technique called abrasive-assisted drilling has been designed and developed to improve the surface finish of the drilled hole wall during the drilling of Al6063/10%SiC metal matrix composites. The developed process eliminates the use of supplementary surface finishing process such as abrasive flow machining or deburring of drilled hole, which adds to the cost of product. With the help of this technique, fine polished drilled hole wall surface can be produced by removing small fragments of material generated by the high-energy abrasive particles. A considerable increase in surface finish of the drilled hole wall has been observed for metal matrix composites. Taguchi’s methodology has been used to explore the effect of input process parameters on the surface roughness and hole oversize of the drilled hole. The input process parameters under consideration are rotational speed, finishing time, abrasive size and abrasive concentration.
In this article, we present a developed bidirectional convergence ant colony algorithm to solve the integrated job shop scheduling problem with tool flow in flexible manufacturing system. In particular, the optimization problem for a real environment, including system make-span and waiting time for tools, has been approached by means of an effective pheromone trail coding and tailored ant colony operators for improving solution quality. The algorithm provides an effective integration between operation sequence and tool selection. A new principle of state transition probability is proposed with consideration of the waiting time for tools, and an optimization method of tool assignment is put forward. The proposed algorithm employs a machine decomposition method inspired by operations that are processed on fixed machines. The ant just gives the partial solution on one machine each time to construct the global scheduling solution with the previous solution on the other machines. This method performs well using the efficiency of ant colony algorithm for solving job shop scheduling problem. The proposed algorithm is tested by a series of simulation experiments, and interpretations of the results are also presented. Final experimental results indicate that the developed bidirectional convergence ant colony algorithm outperforms some current approaches in job shop scheduling problem with tool flow.
Minimum quantity lubrication technology is emerging as a potential alternative to flood cooling to effectively control cutting temperature during machining. In this study, an in-house developed minimum quantity lubrication delivery system has been used for minimum quantity lubrication delivery of cutting fluid at the machining zone. An advanced nanofluid coolant was also used for the purpose of minimum quantity lubrication. Different methods have been attempted to measure the near tool-tip temperature during turning of AISI 4140 steel with multi-layered coated insert under dry, flood cooled and minimum quantity lubrication cooled condition. It was further attempted to identify the best technique for assessing near tool-tip temperature. Infrared thermography has shown the closest result to that obtained through a finite element analysis (DEFORM 3D™) simulation. Potential of multi-walled carbon nanotube–based nanofluid in minimum quantity lubrication application has been thoroughly investigated in this case study, where high-speed turning of AISI 4140 steel was carried out by a multi-layered coated carbide insert. Design of experiments, based on Taguchi method, was used to find out the significance of cutting parameters on machinability under nanofluid environment. Multi-walled carbon nanotube–based nanofluid was found to outperform the rest in all conditions.
This article describes automated identification, classification, division and determination of release direction of complex undercut features of die-cast parts. The proposed system uses the concepts of visibility and accessibility to identify undercut features from a B-rep model of a die-casting part. The undercut features are then classified using a rule-based algorithm. Thereafter, the identified complex undercut features are separated into simple ones. Finally, the release direction for each simple undercut feature is determined and those having common release direction are grouped. The proposed system is implemented on case study die-cast parts, and the results are verified. This article would help bridge the design-manufacturing integration gaps in the die-casting process.
The present study focuses on experimental modelling of travelling wire electrochemical spark machining process using coupled methodology comprising Taguchi methodology and response surface methodology. Experiments were conducted on Pyrex glass workpiece using L27 orthogonal array considering applied voltage, pulse on-time, pulse off-time, electrolyte concentration and wire feed velocity as input parameters and material removal rate, surface roughness (Ra) and kerf width (Kw) as output parameters. The multi-response optimization is also performed using a coupled analysis comprising grey relational analysis and principal component analysis. The optimal process parameter setting demonstrates the enhancement of material removal rate by 154% and reduction of surface roughness and kerf width by 21% and 11%, respectively, against the initial parameter setting.
A piezoelectric polyvinylidene fluoride film stress sensor was developed to measure the contact pressure on the sheet near the cutting edge in the fine-blanking process. Two cases with and without cracks in the fine-blanking surface were studied. The relationship between the contact pressure and crack width was investigated using the Kriging methodology at different punching speeds. The maximum contact pressure appeared at the beginning of sheet punching, but not at the end of V-ring indention. For the case with and without cracks in the fine-blanking surface, one and two fluctuations of contact pressure are observed, respectively. Using the Kriging model, a fine-blanked surface with a reduced crack width can be obtained using the optimal values of contact pressure and punching speed.
The manufacture of polymer components for biomedical applications is an area that has received much attention from polymer scientists, with high levels of wear resistance achieved, but relatively little research has been done into the machining operations required to manufacture the complex geometries used in total joint replacement. Traditional metal cutting theories have been shown to be insufficient for the analysis of polymer machining, as polymers exhibit viscoelastic behaviour, and unique chip formation mechanisms. This article details an experimental investigation into the effect of tooling and machining parameters on the cutting forces, surface roughness and chip formation in ultra-high-molecular-weight polyethylene, a common material used in biomedical applications. This research quantifies the relative importance of each parameter, the chip formation mechanisms and resulting surface roughness for the given machining parameters and provides new insight into applied research on the machining of polymers.
Methodologies for the identification of key characteristics have been widely applied in quality management through the selection of critical dimensions and the measurement of variations. However, methods for both the identification and decomposition of key characteristics have not yet been developed, and more research is still required. In answering this need, a systematic top–down decomposition approach for the identification of key characteristics is proposed. The methodology of the identification and decomposition of key characteristics can be divided into two steps: first is the construction of candidate characteristics, and second is the identification of key characteristics. These steps are based on precise mathematical definitions. Initially, the necessary information for the construction of the candidate characteristics is obtained from analysis based on assembly-oriented graph, and that information is then conveyed utilizing feature adjacency matrix. A concept for a propagation chain is then proposed, and a search algorithm for an auto-generating propagation chain is obtained through feature adjacency matrix. The degree of influence of the candidate characteristics on the key characteristics is then defined. A formula is derived that can calculate the degree of influence by utilizing a variation model. Finally, the process of the identification of the key characteristics is achieved according to the relative degrees of influence. An aircraft boarding gate is presented in order to validate the proposed methodology. Two key characteristics of the aircraft boarding gate are identified, and the results indicate the methodology’s feasibility.
Machining accuracy is the most critical indicator to evaluate the machining quality of parts in metal cutting industry. However, it is difficult to be identified before real cutting, because of a variety of error sources presented in a machining process system, such as assembly inaccuracy of machine tool, deformation caused by temperature variation and dynamic cutting force, tool wear, servo lag and so on. Consequently, it is difficult to determine whether a new machining process can satisfy accuracy requirements beforehand. Traditionally, a machining process is validated through the "trial and error" approach, which is time consuming and costly. If machining accuracy can be predicted to a large extent, a rational process can be planned to ensure the precision of parts and even to maximize resource utilization without trial cuts. For this purpose, this work focuses on machining accuracy prediction for five-axis peripheral milling based on the geometric errors. An error synthesis modeling method is proposed to integrate the geometric errors of the process system, including machine tool geometric error, workpiece locating error, cutting tool dimension error and setup error. From a multi-body system point of view, all these errors are synthesized to generate position error of the cutting contact point in the workpiece coordinate system. Then the machining error is obtained by projecting the position error to the workpiece normal vector, which can be measured by a coordinate measuring machine. The prediction model has been evaluated by a cutting test with our in-house-developed prototype software. The result shows that the proposed method is feasible and effective.
Chemical and mechanical properties of the welded joint are greatly affected by flux composition. The resulting chemical compositions of C, Si, Mn, P and S in the weld metal have been studied using formulated fluxes. The constrained mixture design, extreme vertices design, has been used to formulate fluxes to study the effect of flux constituents. Regression models were developed for weld metal content in terms of individual flux constituents and their binary mixtures for submerged arc welding of high-strength low-alloy steel. From the results, it is found that CaF2 is the most significant flux constituent and Al2O3 is the second most significant constituent among individual mixtures. CaO–MgO and CaO–Al2O3 binary mixtures are the most effective to change weld metal content. Regression mathematical models have been checked for adequacy using t-test and analysis of variance (F-test). Flux mixtures’ composition has been provided for optimum chemical composition of weld metal.
A three-point method based on sequential multilateration is applied to measuring the geometric error components (GECs) of three-axis machine tools (MTs). To meet the accuracy requirement of geometric error mapping, a sequential multilateration scheme is developed for high-accuracy point measurement by introducing four additional targets into the measuring system, and the uncertainty of point measurement is verified by simulation. Three independent targets fixed on the MT’s spindle assembly move along with each axis step by step and their coordinates at each step can be determined by the distance data acquired by laser tracker at all steps based on sequential multilateration. Then the volumetric errors of the three target points can be obtained by comparing the actual coordinates and the corresponding desired coordinates, and nine equations can be established by substituting volumetric errors into the error model of linear axis, so that the six GECs of each axis can be obtained by solving these equations. The three squareness errors can be determined by computing the angles between the average lines of the three axes which are achieved by linear curve fitting. Experiments are conducted to measure these 21 GECs, and the volumetric errors in the three-axis MT’s workspace, which are determined by these measured GECs based on the error model of three-axis MT, are compensated. Finally, the positioning errors of the MT with compensation and without compensation are evaluated by laser interferometer, respectively, the experimental results of which demonstrate that the positioning errors are significantly reduced by the error compensation.
Nickel-based alloys are widely used in applications requiring high strength at elevated temperatures such as in aircraft jet engines. However, nickel-based alloys such as Inconel 100 are still considered difficult-to-machine metal alloys. In this study, specially designed orthogonal cutting tests on Inconel 100 nickel-based alloy have been conducted using WC/Co cutting tool with two varying rake angles, cutting edge radii and at wide ranges of cutting speed and feed. Effects of those parameters on specific forces have been investigated. Serrated and segmented chip formation is observed and the mechanics of segmented chip have been modeled and validated using the experimental test data. Chip microscopic images are utilized in measuring and calculating chip formation angles, shear strain, and shear strain rate in the main shear zone and within the shear bands. It was found that segmentation is highly influenced by machining conditions, and energy distributions calculated with regard to machining parameters reveal that friction dissipation and material separation are significant in machining of Inconel 100 nickel-based alloy.
This study makes a comparison between whisker-reinforced alumina and SiAlON ceramic tools in high-speed face milling of Inconel 718. A series of tests have been conducted, and the cutting forces, tool wear morphologies and tool failure mechanisms are discussed with regard to a wide range of cutting speeds (500–3000 m/min). Results show that the resultant cutting force of SiAlON ceramic tool KY1540 is much bigger than that of whisker-reinforced alumina ceramic tool KY4300 at the same cutting condition. For both kinds of tools, under relatively lower cutting speed, nose notch wear is the predominant failure mode affecting the tool life, while further increase in the cutting speed, notch wear at the depth of cut becomes the determining factor. KY1540 shows a better notch wear and thermal shock resistance than KY4300. The tool failure mechanisms involve notching, microcracks, chipping, flaking, adhesion and oxidation wear. Better surface quality can be got using KY4300 ceramic tools.
The deterministic polishing process is usually used as the final step to produce part surfaces of high surface finish and form accuracy. This article presents the models of the local and the global polished profiles for the deterministic polishing process when a surface is polished by a spherical polisher. The local polished profile is modeled by integrating the index of material removal, which is defined as the polished depth at unit length of the polishing path, at each tool–surface contact region. According to the model, the local polished profile is determined by the process parameters, the tool attitude, the measuring angle and the geometrical/mechanical properties of workpiece and tool. The linear algebraic expression of the global polished profile is derived by convoluting the local polished depth at each dwell point of the polishing process. The polishing experiments are conducted to verify the proposed model in the different polishing conditions. Moreover, simulation results are given to illustrate the application of the proposed model in optimizing the feed rate to minimize the surface form error in the deterministic polishing process.
This article presents an experimental investigation of wire cut electro discharge machining of pure titanium. The marvelous characteristics of pure titanium such as its compatibility and noticeable physical, mechanical and biological performances have led to their increased application in various industries especially in seawater pipings, heat exchangers, implants, prosthesis, airframe and aircraft engine parts over the last 50 years. However, due to low thermal conductivity of titanium and their reactivity with cobalt in most tool materials, there are some difficulties in machining titanium and its alloys by conventional machining. On the other hand, unconventional machining processes especially wire cut electro discharge machining are more appropriate techniques for machining difficult-to-machine materials like pure titanium. This research work is mainly focused on microstructure analysis in terms of machining parameters such as pulse on time, pulse off time, peak current, spark gap using energy-dispersive X-ray, scanning electron microscope and X-ray diffraction techniques. The present results reveal that pulse on time and peak current significantly deteriorate the microstructure of machined samples, which produces the deeper, wider overlapping craters, pockmarks, globules of debris and micro-cracks. The microstructure analysis of rough cut surface was based upon the theory of electrical discharge phase and metallurgical physics.
In this article, friction stir welding experiments were performed on AA 5083-H111 aluminum alloy using a tool with a triangular pin to study the effect of tool rotational speed and welding speed on the ultimate tensile strength, percentage of elongation (), hardness and microstructure. The investigations were done with the optical microscopy, stereomicroscopy, scanning electron microscope and energy dispersive spectroscopy. In the visual inspection, it was observed that some of nugget zones have an onion ring like features and a basin-shaped profile. The ultimate tensile strength and percentage of elongation () of the welds decrease with decreasing the welding speed for the 800 r/min. On the other hand, as the welding speed increases, the UTS and decrease for the 1250 rpm/min, the ultimate tensile strength and percentage of elongation () decrease. The main factor, which affects the reduction in both ultimate tensile strength and percentage of elongation (), is defects in the welds. A comparison of ultimate tensile strength and percentage of elongation () as a function of tool rotational speed for the 100 mm/min showed that both ultimate tensile strength and percentage of elongation () decrease with the increase in the tool rotational speed. The weld efficiency varied between 88.3% and 92% in the defect-free welds. The hardness distribution of the zones on the welds revealed that no remarkable differences exist between them. Hence, the variance on the grain sizes of zones is small.
The springback is one of the major defects associated with sheet metal–forming industry. The objective of this study is to minimize the springback and the process variability in V-bending operation. In all, 11 process parameters, the bending angle, sheet thickness, material type, material texture, punch speed, punch holding time, sheet width, punch radius, lubrication, warm working, and repeat bending, have been considered, and their effect on springback has been studied. Based on Taguchi L12211 orthogonal array design, bending tests were conducted on two types of aluminum sheets (Al 1100 and Al 6061), and investigation was focused mainly on the effect of process variables on the springback. As springback is a process defect, the smaller the better signal-to-noise ratio is utilized in the optimization process. Based on the analysis of variance results, the percentage contribution of each factor to springback was calculated and optimum levels of entire factors were ascertained. The punch holding time, material type, and lubrication were found to be the most significant factors affecting springback. The combined effect of these parameters on springback was about 70%. From the confirmation tests, there has been significant improvement in the standard deviation of the mean value of springback.
Remanufacturing, which processes end-of-life products with disassembly, testing, reprocessing, and reassembly operations in such a way that their quality and performance is restored, has attracted substantial interest in recent years. In this article, we address a capacitated dynamic lot-sizing problem with remanufacturing, in which there are heterogeneous demand streams for newly manufactured products assembled wholly by brand-new components and remanufactured ones reassembled by reprocessed components. The demand for remanufactured products could also be satisfied by new ones, as remanufactured products do not meet self-demand, but not vice versa. For this planning problem, a fuzzy mixed integer linear programming model, which considers the uncertainties of market demands, the quantity of end-of-life products available, the remanufacturable rate, selling prices, unit cost values, and capacity constraints, is developed by triangular fuzzy numbers. After that, the fuzzy mixed integer linear programming model is transformed into a crisp equivalent by clarifying fuzzy constraints and objective. The solution approach is designed by genetic algorithm, in which self-adaptive formula is adopted to resolve difficulty in obtaining optimum value of crossover probability and mutation probability. Finally, a numerical example is suggested to demonstrate the applicability and effectiveness of the proposed model and solution approach.
One of the variants and simplest form of incremental sheet metal forming process is single-point incremental forming in which a spherical ended tool is used to form features on one side of the initial plane of the sheet. Dimensional deviation is observed in the region of component opening (due to sheet bending) and at the wall as well as base regions. This article presents a methodology to minimize the dimensional deviation in the wall and base regions of single-point incremental forming formed components. The authors observed that the sheet deflection due to axial force and tool deflection due to radial force are the two main factors leading to the geometric deviation in wall as well as base regions. An analytical model has been developed for estimating these two deflections. These deflection values are incorporated in the tool path generation, and the components formed using the compensated tool path resulted in acceptable dimensional accuracy in the wall region. Force predictions carried out by force equilibrium method are used to calculate the deflection compensations as its predictions are in reasonably good agreement with the force predictions of finite element analysis and experimental measurements. Significant improvement in accuracy is achieved by using the deflection compensated tool paths.
In the current study, three-dimensional simulation of an autogenous gas tungsten arc welding of β-titanium alloy (Ti-15V-3Cr-3Sn-3Al) was attempted using the finite element method. Models were developed for continuous current and pulsed current welding at different frequencies (2, 4 and 6 Hz). The transient temperature distributions along the heat-affected zone of the simulated weldments were predicted by considering a moving heat source, the surface heat flux distribution and convectional heat loss in the welded plates. Comparative studies of cooling rates and peak temperatures of the simulated welds between all the generated models were conducted. A realistic temperature at the weld center was also predicted. Results show that both peak temperature and cooling rate exhibit increments with pulsing and also with the increase in frequency up to 4 Hz. Obtained results validated against experimental data showed good agreement.
This article investigates the value-adding practices of Manufacturing Engineering for integrated New Product Introduction. A model representing how current practices align to support lean integration in Manufacturing Engineering has been defined. The results are used to identify a novel set of guiding principles for integrated Manufacturing Engineering. These are as follows: (1) use a data-driven process, (2) build from core capabilities, (3) develop the standard, (4) deliver through responsive processes and (5) align cross-functional and customer requirements. The investigation used a mixed-method approach. This comprises case studies to identify current practice and a survey to understand implementation in a sample of component development projects within a major aerospace manufacturer. The research contribution is an illustration of aerospace Manufacturing Engineering practices for New Product Introduction. The conclusions will be used to indicate new priorities for New Product Introduction and the cross-functional interactions to support flawless and innovative New Product Introduction. The final principles have been validated through a series of consultations with experts in the sponsoring company to ensure that correct and relevant content has been defined.
Making real-life decisions regarding selection of optimum parameters in machining of materials, especially when faced with conflicting objectives, is a tough task. Multi-objective methods are usually used to deal with such problems. This article applies grey relational analysis to the multi-responses that were obtained during turning of AISI 304 austenitic stainless steels on a computer numerical control lathe. The experiments were conducted using the Taguchi design of experiments technique. In grey relational theory, a grey relational grade is found such that it indicates an optimum level of machining parameters that produce smaller magnitudes of surface roughness, flank wear, tool vibrations and a higher magnitude of material removal rate. The combination of the following machining parameters produces a better turning performance: speed of 210 m/min, feed rate of 0.15 mm/rev, depth of cut of 1.0 mm and a nose radius of 0.4 mm. The significant factors affecting the overall responses of turning process were evaluated by analysis of variance. Thereafter, optimum values of overall responses were predicted. Finally, a second-order multi-objective model was developed, which relates the machining parameters to the grey relational grade using response surface methodology.
This article aims to present the influence of the measurement uncertainty of a commercial laser tracker on the volumetric verification of a machine tool through the study of verification procedures that are affected by measurement uncertainty, multilateration and laser tracker self-calibration. Self-calibration provides relative positioning between measuring coordinate systems (laser trackers) and the reference system from the measured points of the same mesh. The measured points are affected by the noise of each laser tracker; therefore, they provide positions that are different from the real positions of the laser trackers. By applying the technique of multilateration and by knowing the positions of the laser trackers, the measurement noise can be reduced. The range of the measurement noise reduction is influenced by the radial measurement noise of the laser tracker, the distance between the laser tracker and the measured point and the techniques that multilateration and laser tracker self-calibration employs. This article presents different laser tracker self-calibration procedures, a least squares adjustment, trilateration and quadrilateration as well as the scope and appropriateness of each method relative to the laser tracker measurement noise. Moreover, the influences of radial laser tracker noise on the trilateration and quadrilateration techniques are described as well as the influence of the distance between the laser tracker and the measured point on multilateration.
In industrial applications, particularly in aero, marine and medical industries, titanium has received great attention as a useful material and electrical discharge machining as its machining process. Selection of optimal machining parameters in a multi-objective environment is essential for specific workpiece and tool material combination, which is the concern of industries to improve the overall productivity at less cost. In this article, optimization of critical electrical discharge machining parameters such as pulse current, on time of pulse, off time of pulse and tool geometry depending on the responses such as titanium machining rate, graphite wear rate, surface roughness and deviation between entry and exit while machining titanium grade 5 alloy with graphite tool electrode at negative polarity is presented. Taguchi’s L27 orthogonal array was used to design the experiment with interaction between factors. The weighing method was used to integrate different objectives into one performance. The optimal combination of process parameters was found statistically using signal-to-noise ratios. Significance was checked by analysis of variance. Optimum parameters were found to be pulse current 15 A, on time of pulse 50 µs, off time of pulse 200 µs and cylindrical tool geometry. Resultant percentage improvements in different responses were presented.
The method of embedded cold-pressing joining could achieve the joining of sheets with different thickness and the joining of dissimilar sheets. Besides, it could meet the lightweight request easily. This article expounded the joining mechanism of this method deeply. To expound the joining mechanism of this method, this article has taken aluminum and stainless steel as examples. In addition, numerical stimulation studies of different hole types’ connecting processes had shown that it was easier to reach plastic yield conditions for aluminum and deform it under the same load conditions. The deformation achieved was significantly greater than that for stainless steel. The width increment of the joining parts increased with the increase of the load pressures; however, the thickness changes of the joining parts behaved in an opposite manner. When the pressing volume of the punch reached 2.4 mm, with the width increment of aluminum sheets of the square hole reaching 2.78 mm, which was the maximum width increment, followed by the hexagonal hole, and the round hole being a minimum. Hole type had a small influence on the width of stainless steel sheets. The experimental results of different hole type joining process indicated that compared with round hole and hexagonal hole, the filling of the square hole was relatively difficult. In case of unreasonable process schemes, defects such as "fake joining," "offset loading" and "hole deformation" would occur. Thus, this article provided a theoretical basis for the scheme establishment and quality control of the embedded cold-pressing joining process.
This article presents a novel method to construct an autonomous, intelligent computer-aided design/computer-aided manufacturing programming system for the cutting device controller (e.g. a computer numerical control laser cutting machine tool) based on ant colony algorithm. The computer numerical control cutting device should be able to optimize trajectory autonomously between cutting objects. In order to find the best sequence of operations that achieves the shortest trajectory, ant colony is proposed. The shortest cutting trajectory can be formulated as a special case of traveling salesman problem. The integration of ant colony algorithm and traveling salesman problem can be included in commercial computer-aided design/computer-aided manufacturing packages to optimize the cutting trajectory.
This article proposes a new tube forming process designated as ‘elastomer-assisted compression beading’ that is made from a combination of tube bulging produced by elastomer forming and conventional pressworking compression beading. The presentation includes independent determination of the mechanical properties of the tubes, analytical modelling, finite element simulation and experimentation under laboratory conditions with the aims and objectives of identifying the key operating parameters, understanding plastic flow and failure and establishing the formability limits of the elastomer-assisted compression beading process. Results and observations show that the elastomer-assisted compression beading process is capable of producing sound, large-width, compression beads in a broader range of operating parameters than those currently being achieved by means of conventional compression beading. Applications of the proposed elastomer-assisted compression beading process span a wide range of industrial uses involving attachment of tubes to sheets and damping vibrations in air-pressure lines, liquid systems or exhaust tubes.
In this study, friction stir welding window for AA6061-T6 aluminium alloy based on tool rotational speed and weld speed was developed. The formation of friction stir welding/processing zone has been analysed macroscopically and microscopically. Fracture locations of the joints were also analysed using scanning electron microscope. It has been experimentally found that the joint fabricated using tool rotational speed of 1000 r/min and weld speed of 40 mm/min (obtained from friction stir welding window), tool shoulder diameter of 24 mm with tapered cylindrical pin profile and the ratio of shoulder to pin diameter with value 3 showed better mechanical properties compared to other joints. The developed welding window will be used as ready reckoner to select appropriate rotational and welding speed to fabricate defect-free joints.
The influence of difference in thickness, material properties and the weld zone on deep drawing and stretch forming behavior of tailor welded blanks is a critical laboratory scale study before implementation in car body design. Mostly, various low-carbon steel sheets are used for fabrication of tailor welded blanks due to their excellent weldability and formability, and these steel sheets have high normal and planar anisotropy from preprocessing stage due to large deformation cold rolling. In this study, two different tailor welded blanks and one laser welded blank of similar material combination were fabricated by laser welding of interstitial-free, interstitial-free high-strength and high-strength low-alloy steels. Transverse tensile testing of the laser welded blanks of similar material combination (interstitial free–interstitial free) and two tailor welded blank specimens (interstitial free–interstitial free high strength and interstitial free–high strength low alloy) were conducted to evaluate the weld quality in terms of strength and failure location. The effect of anisotropy on formability of tailor welded blanks was investigated in terms of cup depth and fracture location in cylindrical deep drawing process. Finite element simulations of the deep drawing process were conducted using the commercial available nonlinear solver, RADIOSS. It was observed that the Lankford anisotropy parameter, R-value, influences the thickness distribution, weldline movement and failure location in tailor welded blanks.
Laser bending is an innovative technique to obtain the required bend-angle and sheet metal curvature by means of laser beam irradiation with controlled laser parameters. In this work, a numerical investigation on curvilinear laser bending of magnesium M1A alloy sheets has been carried out. Three-dimensional sequential transient thermomechanical numerical model is developed by using finite element method. The model has been validated by comparing the predicted results with those obtained in the experiments. The curvilinear laser bending process is studied in terms of temperature distribution, stress–strain distribution, bend angle and displacement at the edges. The results showed that the bend angle increases with increase in scanning path curvature. It is observed that the displacement at various edges and final shape of the worksheet are affected by the scanning path curvature. The results will be useful in adjustment and alignment processes and the generation of complex shapes using lasers.
Dual-phase steels are being applied in the automobile sectors for their higher strength with reasonable work hardening exponent. However, applications of these steels in tailor welded blanks for automobile part manufacturing involve laser welding and subsequent sheet forming. The thermal cycle during laser welding changes the local properties of the weld zone, which affects the formability. Hence, the present study was targeted to understand the effect of laser welding in formability of dual-phase steel. Laser welding of 1.2-mm-thick dual-phase steel with tensile strength of 600 MPa (DP600) and 980 MPa (DP980) was performed using 2-kW fibre laser set-up to fabricate two different laser welded blanks. The laser power and scan speed during welding were selected as 1.8 kW and 1000 mm/min, respectively. Weld quality was accessed using microhardness, metallography and transverse tensile tests. Formability of the laser welded blanks was evaluated in terms of cup height by Erichsen cupping test. It was observed that formability of welded blanks reduced compared to parent metals. The soft zone was observed in the heat-affected zone of DP980 welded specimens, and hence, reduction in formability was more. Finite element simulation of Erichsen cupping test was performed using LS-DYNA explicit finite element code.
The ability to predict and evaluate the machining performance quickly and realistically is extremely valuable. In this work, experimental investigations were carried out to optimise and compare the machining performance of physical vapour deposition–applied single-layer TiAlN-coated carbide inserts with chemical vapour deposition–applied multi-layer TiCN/Al2O3/TiN-coated carbide inserts during turning of hardened AISI 4340 steel (33-35HRC). The correlations between the performance measures, namely, three components of cutting force, surface roughness and tool life were developed by multiple linear regression models. The correlation coefficients, found almost close to 0.9 for all the developed models, indicate that the developed models are reliable to predict the responses within the domain of the cutting parameters selected. Tool life was observed to be affected more by cutting speed followed by depth of cut and feed. However, this effect was more prominent for physical vapour deposition–coated tools than chemical vapour deposition–coated ones. Optimum cutting conditions were determined using response surface methodology technique and the desirability function approach. It has been observed that while using physical vapour deposition–coated inserts, benefit of availing lower cutting forces and surface roughness with a sizeable tool life can be obtained by using the cutting speed of 176 m/min and at lower values of feed and depth of cut.
Tool forces and surface finish are often used as measures to evaluate the performance of a machining process. Cutting parameters have their own influence on the forces and surface finish. In this study, the forces and surface finish produced during turning of hardened EN31 steel (equivalent to AISI 52100 grade) have been analyzed. Uncoated cubic boron nitride insert was used as a tool. Regression analysis was made to establish the dependency of force and surface roughness on cutting parameters. The predictions from the developed regression equations were compared with the measured forces and roughness data. Analysis of variance was undertaken to measure the goodness of fit of the measured data. The models, developed for prediction of forces and surface roughness, were found significant. The most significant parameter affecting the forces was the depth of cut. Feed was also found to be a significant parameter. In most of the cases, cutting speed had only a marginal influence. The influence of cutting speed, feed and depth of cut on the forces was studied. A favorable range of the cutting parameter values was obtained for energy-efficient machining. It was also established that for the conditions of most efficient cut, the surface finish produced was reasonably acceptable.
Estimation of the temperature distribution in roll and strip is important for the modeling of rolling process. A number of numerical and analytical methods have been proposed in the literature for the estimation of temperature distribution in rolling. This work proposes a simplified and faster semi-analytical method. A finite element method code is used for the estimation of friction and plastic deformation powers based on partially converged solutions. These powers form inputs to analytical temperature prediction modules. The heat partition between rolls and strip is accomplished by matching the interface temperatures obtained from the temperature modules of strip and roll. The proposed method is validated from the experimental results available in literature, and a good agreement is found. Some parametric study has been carried out based on the proposed method.
As the shapes of stamped parts become more complicated and the trend toward light weight continues, making a stamping die becomes more difficult because of inevitably poor formability. Poor formability can be improved if the material flow during stamping is carefully controlled. The application of a drawbead has become common to retard metal flow into the die cavity at the region where a wrinkle is expected. However, the effects of drawbeads are contradictory; for example, one effect prevents wrinkling and another aggravates fracture. Since the blank’s shape also controls the material flow, the beadless stamping process has been devised. In this process, the role of the drawbead is replaced by the shape of the blank. The author developed a digital tryout that emulates a real tryout process wherein a deformation process analysis has been iteratively carried out with a trial blank and the analysis result is carefully investigated. Since the control variable of the proposed digital tryout is the deformed shape, the trial blank shape that corresponds to the desired deformed shape is determined with an optimal blank design method. The present digital tryout was iteratively performed by changing the desired deformed shape until the analysis results predicted no wrinkling and no fracture. The validity of the proposed method was confirmed through an application using a real automotive part.
Generating product design concepts to meet functional requirements while maintaining a specific brand identity is a daunting task for a designer. Shape grammars have been applied to describe the creation of branded product shapes via a set of shape rules and were manually used to create a family of new design concepts, which maintain the product brand identity. Nevertheless, shape grammars are not able to evaluate whether the generated new product concepts can fulfil specified functional requirements of a product. In this research work, shape grammar is combined with an optimisation technique known as the Bees Algorithm to derive a computational architecture for generating branded design concepts that can meet a specified functional requirement. This combination approach allows shape rules to evolve while evaluating how well the outcomes of the new design concepts meet a specified functional requirement. This paper describes how the combination of the Bees Algorithm with shape grammar is created to generate branded product concepts, and shows that this approach can outperform a combination of shape grammar with an evolutionary algorithm.
Multi-weapon production planning contains multi-objective combinatorial optimization and decision-making problems with the NP-hard and large-dimensional natures, which are difficult to be attacked by one single technique successfully. A four-stage hybrid approach is proposed to solve this problem. In the first stage, the multi-weapon production planning problem is formulated with 2N (N > 5) objectives based on operational capability requirements and expected downside risk measure. In the second stage, the formulation addressed is converted into a bi-objective optimization model using goal programming. In the third stage, an algorithm DENS based on differential evolution and nondominated sorting genetic algorithm–II is developed to obtain the Pareto set. Finally, the multiple attribute decision-making method technique for order preference by similarity to ideal solution is employed to acquire the compromise solution from the Pareto set. A case study is given to demonstrate the effectiveness of the proposed approach. The concrete advantages of goal programming, DENS, and technique for order preference by similarity to ideal solution are also validated in this case. This approach can support the weapon production planning in defense manufacturing and is also applicable to solve the multi-level and multi-objective problem in other manufacturing fields.
With the rapid development of the modern manufacture, a radio frequency identification–based tracking network has been gradually established to monitor and track the material flows in a job-shop floor. Based on an event-driven graphical schema, this article puts forward a new method for modeling and analyzing the job-shop-type work-in-process material flows tracking network. The schema elements are mapped into the network nodes, and the association relationships among the elements are mapped into the network edges. Furthermore, corresponding measures and metrics are presented to evaluate the work-in-process material flows tracking network performance. Finally, a simple example is given to verify the feasibility of the proposed method. It is expected that this study will provide a systemic evaluation method for guiding and optimizing the radio frequency identification–based tracking configuration solution for job-shop-type material flows.
Automatic tool selection in milling operation has become a very important step in the manufacturing and planning processes for 2.5D piece machining. The main contribution of this article is the development of a new method based on directional morphological approaches, applied to automatic tool selection in computer numerical control milling machines for machining a 2.5D of a geometry piece provided of three-dimensional model of computer-aided design or from an image taken with other devices. First, the image is preprocessed by applying several image processing techniques. Later, mathematical morphology as erosion or dilation to create structural element with the shape of the cutting tool is used. The method displaces a structural element throughout the entire image with the values of the lengths of the piece boundary and the cutting tool to select the correct cutting tool and tool path. Besides, with the same structural element, the zig and zig-zag contour trajectories are obtained in standard computer numerical control code. Results from these experiments show that the method makes it possible to obtain good performance in automatic tool selection when several types of pieces are processed.
The factors that affect the life of continuous steel casting rollers were investigated. Rollers that were removed from a manufacturing line because they had failed were renovated by submerged arc welding and subjected to working conditions until they again failed. The welding parameters (welding current, welding voltage, welding speed, current polarity, preheating temperature, interpass, postheating, and cooling conditions of clad) and chemical reactions and compositions had important effects on roller lifetime. Chromium has a dominant influence on the abrasion resistance of hard martensitic structures of the roller. Cr produces several types of precipitates (M3C, M23C6, M7C3, and M3C2). Alloying elements Mo and V in welding wire form fine carbides Mo2C and VC in weld layers. In low-carbon welding wires, precipitation hardening by N2 is used, by formation of chromium nitrides CrN and Cr2N. This article analyzes the process of failure of the functional surfaces of the repaired roller, in order to identify the origin and propagation of the cracks and share of corrosive environment on the tribo-degradation processes.
Plunge milling is used increasingly in the manufacture of molds and dies for opening pockets due to its advantages over end milling. Because it is a rough operation, it involves high material removal rates and strong cutting forces. In this context, this article reports on a study of the static and dynamic behaviors of the forces involved in the process. In addition, a cutting force model is developed based on the kinematics of the process and the tool’s special features to predict the mean forces generated during the plunge operation. Low sensitivity of the static force components of tool flank wear and minor influence of the system on the dynamic behavior of the process are observed. The model shows good agreement with experimental results.
In this study, three samples of aluminum alloy with 5%, 10% and 15% SiC composites were fabricated using stir casting process. These samples were investigated using scanning electron microscope equipped with energy dispersive X-ray analysis system, X-ray diffraction analysis and differential thermal analysis techniques. Mechanical properties like hardness, ultimate tensile strength and impact strength of these samples were also investigated. The results revealed that a full homogeneous dispersion of SiC particles in aluminum matrix was obtained without addition of any wetting agent. The peak in the X-ray traces corresponds to the presence of aluminum and SiC and the absence of any significant reactive constituents. The differential thermal analysis curve showed an endothermic peak in aluminum matrix between 648 °C and 650 °C with a nil degradation of material. It was concluded from this study that improvement in mechanical properties of three samples has been achieved. Sample 3 with 15% SiC shows a maximum hardness value (Vickers hardness number) of 120, ultimate tensile strength of 190 MPa and impact strength of 18 J.
5S practice follows structured 5S activities from structurize, systematize, sanitize, standardize, and self-discipline to deal with scene management in shop floor control, and it is regarded as the most troublesome aspect with respect to environmental safety and health for a semiconductor manufacturing fabrication. The improved action items for 5S activities can amount to thousands from messy paper filing to untightened chemical piping. However, there is no clear key performance indicator to evaluate how good (safe) the fab is and how to be good (safe) for 5S practice. Failure modes and effects analysis is an effective and efficient way to deal with risk assessment for 5S activities and to prioritize the action requests from the improved result of continuous improvement. However, when failure modes and effects analysis is applied to the risk assessment of 5S audit, the conventional risk priority number lacks of all comprehensive information and misleads to a bias for not considering weights of severity (S), occurrence (O), and detectability (D). In order to improve the method of risk priority number evaluation, this article combining 2-tuple fuzzy linguistic representation model and weighted geometric averaging operators to quantify 5S audit findings is proposed to eliminate the bias from different 5S auditors. This is the first approach for the numerous 5S action items to be quantified and prioritized with resource constraints to sustain 5S practice robust. A case study in a fab was demonstrated to show how the model was implemented to approve its validity.
Deformation under external and clamping forces is an important factor affecting fixture performance. To reduce the deformation of the workpiece–fixture system and improve the performance of the fixture, an optimisation method for the fixture layout and clamping force plan is constructed in this article. First, the workpiece–fixture is illustrated as an elastic–elastic contact model with friction in which the workpiece is modelled by the finite element model, while the fixel can be modelled by either the spring model or finite element model. To accelerate the computing speed of solving the contact problem, a matrix size reducing method for the finite element model stiffness matrix is proposed, utilising less computer memory. Based on the same idea, a clamping force optimisation method considering the friction effect is presented to achieve the optimal clamping force of a special fixture layout within very few finite element model computing processes. Then, based on these, an integral fixture layout and clamping force optimisation algorithm are built by genetic algorithm. At the end of this article, numerical examples are taken to prove the performance of the methods. The results show that the accelerating method yields sufficient performance, and the optimisation algorithms of both the clamping force plan and the fixture layout design achieve favourable convergence.
A grey relational analysis is a novel technique for forecast, developing relational analysis and in decision-making in numerous areas of manufacturing or production processes in industry. In this investigation, an attempt has been made to optimize input process parameters considering assigned weight fraction of output quality characteristics using grey relational analysis. The output quality characteristics considered are thrust force, torque and surface roughness under the experimental domain of cutting speed, feed, step diameter and point angle. The drilling experiments were designed as per Taguchi design of experiments using L9 orthogonal array. The combined methodology of orthogonal array design of experiments and grey relational analysis was implemented to establish the best possible input process parameters that give minimum thrust force, torque and surface roughness. The results reveal that with the help of grey relational analysis, output quality characteristics can be enhanced efficiently.
A design optimization of deburring tools for intersecting holes is presented based on design of experiments and response surface methodology. A deburring tool with hemispherical cutter head mounted on a pivoted shaft was used to deburr intersecting holes easily and quickly. Due to the vibration of the tool during deburring, however, the surface of the deburred edge showed considerable irregularity. Tool dynamics was modeled with ADAMS software with the user-defined subroutines. Based on design of experiments and response surface methodology, the tool design was optimized with respect to tool vibration. Deburring tests with the optimized tool on Al6061-T6 specimens showed significant reduction in surface irregularity represented by an index value change from 1.3 to 0.7 mm.
Microgrooving on crystalline germanium (Ge) <<?h -1.3?>100<?h -0.9?>> surface using 1064 nm wavelength ultrafast laser pulses under ambient condition is investigated. The interaction of laser and target material and the influence of processing parameters such as laser power, pulse repetition rate and scan speed on the groove dimensions and surface roughness are studied. For the laser radiation fluence range used (0.4–0.8 J/cm2), material removal is primarily controlled by optical penetration depth. The depth and width of grooves increase with laser power. In multipulse irradiation, heat accumulation due to residual thermal energy from successive laser pulses results in a greater material removal. Furthermore, groove depth and width decrease as the pulse repetition rate increases from 0.5 to 2 MHz, due to the decrease in pulse energy with an increase in repetition rate causing ablation threshold fluence to move towards the central portion of the Gaussian pulse. Surface roughness has not shown significant changes for the parameters used in this study. A micro-Raman analysis of groove surfaces reveals a change in the crystallinity of the Ge due to laser irradiation.
Micro features are generated on SS-304 stainless steel by electrochemical micromachining. This research aims at the development of best method of micro profile generation for micro components based on electrochemical micromachining in terms of reduced taper angle, overcut, edge deviation and time of machining using cylindrical micro tool. Sinking and milling method is a new approach to microchannel generation, where a micro tool moves vertically to final depth or required depth of machined feature followed by milling along the path of the micro features. The experimental study of process parameters such as pulse frequency of applied voltage, electrolyte concentration, pulse width, micro tool feed rate, machining time and depth of sinking by micro tool is conducted for the investigation and comparative analysis of their effects on material dissolution during micro profile generation utilizing scanning layer-by-layer method as well as sinking and milling method. Machining zone has been simulated in two positions of micro tool, and it has been established that taper less through microchannels can be generated by the scanning method and the sinking and milling method. Complex taper less micro features such as channel net, "U" shape and "S" shape were machined. Micro profile of narrow entry width of 32 µm was machined on 50-µm-thick SS-304 sheet. Very narrow micro profile of 23 µm was also machined on 35-µm-thick SS-304 sheet by the fabricated micro tool of = 8 µm utilizing the new approach of sinking and milling in electrochemical micromachining.
Setup planning and fixture design are two main tasks for the integration of design and manufacturing process. Setup planning identifies which features must be machined in each setup and determines locating datum for each setup, whereas fixture planning determines precise locating and rigid clamping of workpieces according to a part design and process requirements. So, a close interaction exists between setup planning and fixture design. This research deals with the problems of setup and fixture planning for the machining of prismatic parts. In the first step, a new heuristic method is presented to plan the setups with accurate respect to datum faces in design and manufacturing. Two concepts, namely, "inferiority face" and "control face," have been used for this purpose. In the next step, a mathematical model is used to define the primary, secondary and tertiary fixture planes with respect to locators’ position. This model determines relationship between misplacement of locators and dimensional and geometrical specifications of workpiece. The main purpose of developing the model is to determine the effect of locator height error on hole position tolerance. The capability of this model is verified by simulation in "motion study" module in SolidWorks software. This approach is very useful in the hole-making process. The system is developed in Visual Basic on a SolidWorks platform. The effectiveness of the system is verified by an industrial component.
The duopoly model with a Cournot form under random yield has received little attention. This article revisits the classic Cournot duopoly competition model by considering manufacturer yield uncertainty. We analyze the model under symmetric, asymmetric and monopoly situations. The manufacturers’ best production policy and expected market share are compared with each other in each situation. The expected market outputs of the three models are also compared under certain conditions. In the asymmetric case, the asymmetric model is extended by considering a powerful oligarch who can exert influence on her rival’s production decision by releasing her cost-type information. We derive that the maximization of the stronger manufacturer’s expected profit is highly correlated with consumer surplus. Numerical examples are presented to illustrate the results.
Recently, mesh surfaces have become the focus of considerable interest due to its simplicity for data exchange and geometric computation. However, for mesh surface machining, there are few tool path planning strategies but iso-planar method. In this article, a contour-parallel tool path method is presented for machining complicated mesh surfaces with holes or islands by introducing a so-called one-step inverse approach based on physical plastic deformation of metal materials. By rapidly simulating for the inverse forming process of sheet metal of auto-body panels, the machined surfaces are flattened into its initial flat blank on which the cutter contact points are calculated by iteratively offsetting the inner and outer contours of the blank. Then, using the mapping from the machined surfaces to the blank as a guide, the planar offset curves without self-intersection are inversely mapped onto the original mesh surfaces, forming the final contour-parallel tool paths. Benefiting the flattening method based on one-step inverse approach, the task of generating tool paths is reduced from a physical surface to a plane so that geometric computation of tool path generation is greatly simplified, especially for self-intersection elimination in offset curves. Moreover, a new data structure of offset curve is also introduced, which is used to effectively compute the self-intersections. The proposed method has been tested on several sample surfaces, and the experimental results show that the proposed method can deal with complicated mesh surfaces with holes or islands and is also more efficient compared with the traditional methods.
The primary causes of defects in planed timber surfaces have been identified to be cutting tool inaccuracy and forced vibration during the machining process. It is noted that the current mechanical methods used in the woodworking industry to improve surface finish quality have disadvantages that defeat their original attractiveness. This article describes a mechatronic approach used to compensate for cutting tool inaccuracy in wood planing via cutting tool trajectory modification. The approach is based on real-time measurement of the angular spindle position, coupled with periodic vertical displacements of the rotating spindle. A small-scale wood planing machine, which has an actively controlled spindle unit, has been designed for practical investigation of the technique. Experimental results show that the dynamic performance of wood planing machines, and hence the surface finish quality, can be improved via this approach.
In machining, there exist different quality characteristics that define overall process quality. These quality characteristics are controlled by different input process parameters. Thus, for best possible process quality, optimization is required. The resultant quality characteristics have different weightage of preference depending upon the requirements of the individuals or group. If in a group, the individuals have conflicting interests, it becomes difficult to take decisions. In this article, a new hybrid approach for multi-criteria optimization has been proposed based on the user’s opinion/preference while defining quality characteristics. Accordingly, the new technique may be termed as ‘User’s Preference Rating’ method for optimization. The major advantage of this method is that any number of opinions of the individuals can be considered for calculating the weights. Furthermore, in this technique, it is not essential to specify relationship between all quality characteristics. The implementation of the technique has been illustrated using data during ultrasonic machining of titanium.
A hybrid-type three-dimensional visual alignment system is suggested, which is to align pattern mask and glass panel for manufacturing flat panel displays. In order to compensate for the spatial misalignments between mask and panel, a pair of decoupled positioning mechanisms are adopted, where the lower 4-PPR parallel kinematic machine provides 3-degree-of-freedom motions to the pattern mask like the current in-plane alignment systems, while the upper 4-RPS machine gives an independent 3-degree-of-freedom mobility to the glass panel along the directions excluded in the mask movement. Hence, the combinatorial motion of the two positioning mechanisms completes a spatial mask–panel alignment. In this article, two fundamental issues are solved for the operation of the hybrid alignment system. First, the inverse kinematic solutions for the hybrid parallel mechanisms are derived to determine the displacements of active joints for an arbitrary misalignment in the task space. Second, it is developed how to extract the spatial misalignment between mask and panel in real time in terms of three in-plane cameras and the focus value Gaussian model.
The difficulty of obtaining a useful cost estimate at the design stage has long been acknowledged. Data for new products are hardly available and product specifications are often expressed as a range of values; yet, only limited progress has been made to date to improve the quality of the average cost estimate at the conceptual design stage. The aim of this research is to improve the quality of the cost estimate (average cost) at the conceptual stage of design to assist designers to consider cost as a critical factor in selecting the most appropriate design concept. This research investigates the use of Taguchi’s orthogonal array approach to reduce the variation in the product specification (when expressed as a range of values) in order to improve the quality of the average estimated cost for each concept at the conceptual stage of design. A new process has been created, and to validate the process, an industrial case study has been undertaken.
The increasing demand for green products and strategies has led to research on reducing manufacturing costs and energy consumptions. In this study, the brazing method was applied to the fabrication of a micro-end-mill for printed circuit board manufacturing, and the machining properties of the fabricated tools were experimentally investigated. A tungsten carbide cutting edge was brazed onto a stainless steel shank using silver filler, and this material rod was fabricated into a micro-end-mill with a diameter of 800 µm. Machining results for this micro-end-mill were observed via scanning electron microscopy, and an abnormal wave pattern was observed on the cutting surface when using the brazed tool. The woven structure of the workpiece is thought to be the cause of this phenomenon; the wave pattern can be removed by controlling the machining conditions. Since the brazing technique is readily applicable to micro-scale cutting tools, it is expected that these results will contribute to improved machining quality when using brazed micro-cutting tools, as well as improved manufacturing efficiency.
This article addresses reliability evaluation for a production system with intersectional lines and multiple reworking actions, where the reliability is the probability of demand satisfaction. First, the production system is constructed as a capacitated-flow production network by the revised graphical transformation and decomposition techniques. Capacity analysis is implemented to determine the input flow of each workstation subsequently. Second, two algorithms, including a general algorithm, are proposed to generate all minimal capacity vectors that workstations should provide to satisfy demand. The reliability is derived in terms of such vectors accordingly. A real-world case of printed circuit board production system is utilized to demonstrate the performance evaluation procedure.
The prediction of thrust force and torque in drilling remains a key issue. There are three main ways to determine these forces based on experimental, numerical and finally analytical approaches. The major drawback with numerical and analytical methods concerns their reliability compared to phenomenological models. As a consequence, several studies use a resetting method in order to correct parameters of their analytical or numerical models so that they correspond to experimental results. The goal of this article is to introduce a new analytical model in drilling based on the discretization of the cutting edge. Local forces are estimated with a semiorthogonal analytical model based on a modified Merchant’s model. Parameters have been identified by a basic semiorthogonal cutting test for a large range of cutting speed and feed rates, by friction tests for a range of sliding velocities and by a variable shear angle model. The macroscopic feed force and torque are estimated by the sum of each local force along the cutting edge. Two drills applied in a large range of cutting conditions are investigated to validate this approach.
The alternative use of electrical discharge grinding and abrasive grinding, which is applied with the application of slotted wheel named as slotted electrodischarge abrasive grinding, is much suitable for machining of metal matrix composites. But the selection of process parameters is a difficult task due to the complexity of the process. The aim of this study is to optimize the process parameters of slotted electrodischarge abrasive grinding process using a combined approach of artificial neural network and nondominated sorting genetic algorithm II. The artificial neural network architecture has been trained and tested with experimental data, and then the developed model is coupled with nondominated sorting genetic algorithm II to develop a hybrid approach of artificial neural network–nondominated sorting genetic algorithm II, which is used for optimization of process parameters. During experimentation, the effect of current, pulse on-time, pulse off-time, wheel speed and grit number has been studied on material removal rate and average surface roughness (Ra). The results have shown that prediction capability of artificial neural network model is within the range of acceptable limits. The developed hybrid approach of artificial neural network–nondominated sorting genetic algorithm II gives optimal solution with correlation coefficient of material removal rate and Ra as 0.9979 and 0.9982, respectively.
Large-aperture diffraction gratings are the key elements for high-power petawatt-class laser facility. At present, it is difficult to directly manufacture high-accuracy large-aperture gratings by using ultraprecision manufacturing techniques. Mechanical tiling technique with segmented gratings can be employed to cope with the challenge in large-aperture grating manufacturing. In this article, a novel tiling and adjusting device for obtaining large-aperture gratings was proposed and built to overcome the challenges in developing a Big Science Facility. The idea of integrated design and precision analysis has been introduced into the design process of the device. The theoretical analysis on static and dynamic characteristics has been conducted on the key components of the device by using finite element method. Under a series of mechanical tests, the performance of the large-aperture grating tiling and adjusting device developed was evaluated against the industrial requirements. The testing results show that the device has the positioning precision and stability in light of the design specifications. The results also indicate an optimal linear accuracy of 20 nm and a rotational accuracy of 0.4 µrad being achieved at the device.
Dielectric fluid is one of the major components of electrical discharge machining. In this article, the influence of two dielectric fluids on the surface properties of workpiece was investigated. Machining was conducted on the titanium alloy (Ti-6Al-4V) with the new Cu-TaC composite electrodes under the two dielectric fluids, which are the urea solution and distilled water. Cu-TaC electrodes were produced from copper and tantalum carbide powders by powder metallurgy method with 50/50% composition at compacting pressure of 24.115 MPa. The main objective is to compare the effect of these dielectric fluids on the electrical discharge machined surface properties—microhardness (Mh) and surface roughness (Ra). The machining variables used to investigate the Ra and Mh were peak current and pulse duration. The surface roughness was found to be generally higher in the specimens machined with urea solution dielectric fluid, the highest being 19.05 µm. For the specimens machined with distilled water dielectric fluid, the highest Ra is 14.45 µm. The highest microhardness improvement ratio attained by the specimens electrical discharge machined with urea dielectric fluid is about 48% higher than those machined with distilled water. It is concluded that distilled water dielectric fluid gave better surface roughness, while the urea dielectric fluid provides the machined surface with higher microhardness.
Large-aperture lenses are widely used to improve optical resolution and enlarge field of view of a precision optical system, and reasonable mounting can result in higher optical performance. Flexure mounts are usually utilized to minimize distortion of the lens under its own weight and must be accurately assembled so as to provide uniform support loads for the lens. The supporting loads produced by flexure mounts are difficult to be identical because of various uncertainties during assembly process, such as human operation and tool resolution. These nonuniform supporting loads may generate asymmetric deformation of the lens and deteriorate its performance. It is essential to explore the influence of uncertainty supporting loads on the optical performance. A Monte Carlo analysis method is proposed to investigate the optical performance of a lens under uncertainty supporting loads at different load levels. Patran Command Language is used for repetitive calculation of finite element model with random sample of supporting loads. The optical performance responses, such as the surface peak-to-valley and root-mean-square errors and Zernike coefficients, are calculated by fitting the surface deformation data, and their stochastic properties are researched by statistical testing. Consequently, the critical variation range of uncertainty supporting loads considering assembly process can be determined based on Three Sigma theorem with specific optical performance requirement. The results can be used to assign appropriate tolerance of flexure mounts during assembly and to optimize the supporting system of a high-precision optical system.
Design by analogy is a powerful technique for new design solutions. In the literature, there are two possible approaches. The first is more user-friendly but is low structured. The other is more complex, which structures the problem better but is highly time-consuming. This article presents a simple system for structuring the design-by-analogy method, which is based on the abstraction of the problem. The application of these solutions resulted in an increase in design possibilities. Results were collected in a repository, whose order is based on functional logic. The proposed technique was tested on the conceptual phase in the design of novel grippers. The application resulted in the development of innovative grippers. The process can be extended to many different fields. The method can be used as a creativity support during the design phase, also creating repositories that can be enlarged and reused for different applications.
In ultraprecision machining for microchannels, deformation occurs with high frequency because the diamond tool pushes against the channel structure during the machining process. Conservative cutting conditions decrease the cutting force and avoid deformation, but they reduce productivity. Therefore, it is important to select suitable cutting conditions in practice. This article presents a theoretical decision model for optimum machining conditions in manufacturing rectangular micropatterns. The model involves the prediction of cutting force and deformation. To forecast deformation phenomena, a rectangular pattern was considered as a cantilever beam with a distributed load, and the maximum principal stress that acts on the rectangular micropatterns could then be determined. For verifying this solution, several experiments were carried out to obtain a rectangular pattern by single-point diamond turning. Finally, the machining condition decision model was implemented and verified in practice.
This article examines the relationships between the quality of a machined component and the non-intrusive measurements that can be made during the manufacturing process. For the purposes of this study, the overall quality of a machined component is defined by the surface finish and any residual stress induced by the machining process. The focus of the work involves turning of difficult-to-machine metals and non-intrusive measurements recorded during machining. These measurements were acoustic emission, cutting forces and cutting insert temperature. An austenitic stainless steel was chosen as a commonly available metal whose high work-hardening rate and ability to strain transform to martensite make it potentially difficult to machine. Tests were carried out under different cutting conditions to promote thermally and mechanically induced residual stress and variations in the surface finish. Analysis of the mean frequency of the acoustic emission signal has made it possible to determine whether thermal or mechanical interactions dominate the machining process. The mean frequency of the machined samples provided evidence of a thermally driven process. This was confirmed by the close relationship between cutting insert temperature and component residual stress. The analysis of low-frequency acoustic emission generated during machining (below 100 kHz) identified poor surface finish derived from vibrations of the cutting insert.
Optimal component tolerances can reduce product cost and improve enterprise competitiveness. In order to obtain optimal tolerances accurately and efficiently, analytical methods are applied to solve tolerance optimization model. In this article, both manufacturing cost and quality loss are included in the total cost, and two kinds of constraints, including assembly tolerance constraint and process accuracy constraints, are considered in the tolerance optimization model. In order to allocate the optimal tolerances among the related components, the following procedure is presented. First, the two kinds of constraints are ignored, and analytical method is applied to find the initial values of component tolerances. If the initial component tolerances cannot satisfy assembly tolerance constraint, the Lagrange multiplier method is executed and the Lambert W function is applied to solve the corresponding equations to obtain the new values of component tolerances. Then, process accuracy constraints are satisfied through the adjustment of component tolerances. Finally, an example is used to demonstrate the effectiveness of the method proposed in this article.
Aerospace material Inconel 718 is well known for its poor machinability. This article presents an experimental study of the cutting forces in high-speed dry milling of Inconel 718 using a milling cutter with coated carbide inserts. An assessment of the cutting force variations is conducted using statistical approaches and wavelet decomposition taking into consideration the dynamic effects. The averaged peak force values, the peak force variation range and distribution, and the skewness are evaluated. It shows that cutting speed does not have a significant influence on the averaged peak cutting force for the range tested. The tool–workpiece vibrations at the cutter entry stage and exit stage are generally more significant. Moreover, wavelet packet decomposition at level 3 with the DB4 wavelet and Shannon entropy is found to be an effective approach to identify the chatter onset.
A numerical model, developed for LS-Dyna solver, aimed to study the wedge rolling process is presented in this article. In addition, a comparison is made between the experimental and simulated results in order to set up the numerical model’s definition and simulation parameters. The computational performances are evaluated throughout this article to identify the best practice parameters for cold rolling numerical analysis using wedge tools. For an evaluation of the performances of the numerical model, an experimental system was developed to analyse the process parameters of the complex profiles with grooves formed by wedge tools. The methodologies used to record and evaluate the experimental results and the capabilities of the technique are discussed. For a complete analysis, the material behaviour is described by using a five-parameter strain-hardening law. Both the radial force (process force) and the micro-hardness were measured using the Vickers method on a radial section of the rolled piece. The issues addressing the numerical simulation can be extrapolated to other processes (e.g. riveting, flow forming) as this article provides the required information for the development of reliable numerical models.
Creep age forming is often carried out under vacuum or autoclave loading conditions, where a sufficiently high, uniform pressure is required to force the workpiece into close contact with the tool surface. However, many creep age forming tests are performed to evaluate springback by clamping the workpiece to both ends of a cylindrical tool and forcing it to the tool surface, which is different from reality. In this study, a set of mechanistically based unified creep ageing constitutive equations have been incorporated into the commercial finite element code ABAQUS and used to analyse a common creep age forming tester, which employs a cylindrical tool shape. Two loading conditions are investigated: (1) end clamp and (2) uniform pressure. The amount of springback has been predicted, compared and analysed for both loading cases. A method has been introduced to assess the local curvature and springback variations. Good contact was achieved between the workpiece and tool surfaces for the uniform pressure condition (except at the plate end), providing that sufficient pressure was applied. However, for the end clamp condition, contact was limited to the vicinity of the clamps.
The benefits of cryogenic cooling by liquid nitrogen in cutting of titanium alloys have often been evaluated as a comparison to dry machining conditions. However, it is more interesting to quantitatively assess the performance of cryogenic conditioning of the process with respect to standard industrial conditions, that is, with respect to flood emulsion cooling. The technical and scientific literature is scarce and somehow contradictory, especially in terms of cutting forces and coefficient of friction. The aim of this article is to enrich the common base of experimental data, by conducting a comparison of traditional and cryogenic turning of Ti6Al4V in a region of cutting parameters particularly relevant to the aerospace industry, where no previous data are available. This study confirms that cryogenic machining is able to increase the tool life, even with respect to wet cutting. Besides, the results show that not only cutting forces are reduced but also a small, albeit significant, reduction can be achieved in the coefficient of friction at the tool–workpiece interface.
Belt finishing has been tested successfully as a complementary process to hard turning. This technology improves the surface texture and generates compressive residual stress. However, the mechanisms and characteristics of this new process have not yet been fully explained. This article provides a comprehensive characterization of cutting mechanisms generated by belt finishing. First, an analytical analysis based on cutting forces is developed. Then, the macroscopic specific energy is dissociated into a cutting specific energy responsible of shearing and ploughing mechanisms and a sliding specific energy due to adhesion. It has been demonstrated that cutting is more predominant than sliding in belt finishing process. The omnipresence of cutting demonstrates the effectiveness and the profitability of belt finishing operation.
Aiming at the phenomenon of bottleneck shifting in job shop, this article presents the findings on the coupling relationship among the bottleneck shifting factors. We first defined the chain probability to show the relation that the change of one bottleneck shifting factor causes the changes of other factors in job shop. Then, we used three variables (time-capability, time-load, and quality-assurance) and the transaction probability to describe the changes of the factors. Considering the interaction among the bottleneck shifting factors, we established the independent contributions and comprehensive contributions, showing how the changes of various shifting factors may impact the bottleneck shifting phenomenon interactively. Finally, an instance of analysis of the coupling relation of several bottleneck shifting factors in some job shop is given to test the validity and rationality of the method established in this research.
This article presents an approach related to the dissimilar friction stir welding of AA6082 and AA7075. The effects of tool type, tool rotational speed and welding speed on the ultimate tensile strength (UTS) and percentage of elongation were investigated using grey relational analysis and then the optimal combination was determined. The results of a series of analyses revealed that the tool type 4, a tool rotational speed of 1000 rpm/min and a welding speed of 100 mm/min correspond to the optimal condition. Except for tool rotational speed, the other factors are significant at 95% and affect the grey relational grade value with a percentage contribution sorted in descending order as welding speed (48.7%), tool type (27.48%) and tool rotational speed (15.13%). A confirmation experiment was carried out to verify the optimised parameters. The result indicated that an improvement was achieved in ultimate tensile strength and percentage of elongation.
When used in pocket roughing, both the direction-parallel and the contour-parallel tool path strategies usually create critical cutting regions in corners and narrow slots, which can be problematic to machine. The utilization of a trochoidal tool path has been proposed recently in order to avoid these problems. In this work, a method for generating trochoidal tool paths for 21/2D pocket milling using a medial axis transform is proposed. In order to achieve this goal, first the pocket and islands are represented as polygons, and the medial axis transform is calculated as a series of points. The points are then sorted and grouped by an algorithm that generates the trochoidal path whenever the desired radial depth of cut is attained. In the proposed method, machining time is reduced through a pixel-based simulation, adjusting the tool path to the remaining material. The tool path generation method allows the control of the maximum radial depth of cut, avoiding the momentary increments in radial depth of cut, since those increments are problematic when machining hard materials or when high speed machining. Also, a cutting tool selection and area segmentation method using different tool sizes are used.
In this study, continuous microcrystalline diamond layer with grain size of 0.8–2 µm, nanocrystalline diamond layer with grain size less than 100 nm, diamond-like carbon layer with no apparent grains and TiAlN layer with small particles on the top surface are successfully deposited on cemented tungsten carbide-cobalt (WC-Co) samples and microdrills. Diamond peak of microcrystalline diamond film is quite definite in the Raman spectrum, while that of nanocrystalline diamond and diamond-like carbon coating is not so apparent. The roughness of microcrystalline diamond, nanocrystalline diamond, diamond-like carbon coating and TiAlN coatings is about 215.83, 144.4, 23.63 and 168.17 nm, respectively. Nanocrystalline diamond film exhibits lowest adhesive strength between substrate, while diamond-like carbon exhibits highest adhesive strength between substrate. Tribotests show stable friction coefficients of microcrystalline diamond, nanocrystalline diamond, diamond-like carbon and TiAlN coatings as about 0.28, 0.08, 0.08 and 0.4, respectively, while their wear rates against Si3N4 balls are 4.9E–7, 7.0E–7, 7.7E–7 and 2.9E–6 mm3 N–1 m–1, respectively. Microdrilling experiments show that the tool life of microcrystalline diamond–coated microdrill is as about 1.5, 2, 6 and 9 times more than that of nanocrystalline diamond-, diamond-like carbon-, TiAlN-coated and uncoated microdrills, respectively. The main wear types of these microdrills are flank wear, chipping and coating delamination. The results show that the microcrystalline diamond film is more suitable to be deposited on microdrills than the other three coatings to enhance cutting performance of microdrills in dry machining of graphite.
For high-speed machining, the position commands from the trajectory-controlled algorithm should be as smooth as possible since even a small discontinuity in position command may lead to vibrations of the mechanical structure and the servo system. A simplified mechatronic model was proposed to analyze the impact of the trajectory-controlled algorithm on the performance of high-speed machining. The effects of the control loop parameters and natural frequency of mechanical structure on the vibration were also studied. Experimental tests on the vertical z-axis of a high-speed machining center indicate that the presented methodology is able to evaluate the evolution of the vibration due to the trajectory-controlled algorithm, and it is also helpful to choose the suitable controlled parameters for improving the mechatronic performance of high-speed machining.
Digital manufacturing techniques can simulate complex assembly sequences using computer-aided design–based, ‘as-designed’ part forms, and their utility has been proven across several manufacturing sectors including the ship building, automotive and aerospace industries. However, the reality of working with actual parts and composite components, in particular, is that geometric variability arising from part forming or processing conditions can cause problems during assembly as the ‘as-manufactured’ form differs from the geometry used for any simulated build validation. In this work, a simulation strategy is presented for the study of the process-induced deformation behaviour of a 90°, V-shaped angle. Test samples were thermoformed using pre-consolidated carbon fibre–reinforced polyphenylene sulphide, and the processing conditions were re-created in a virtual environment using the finite element method to determine finished component angles. A procedure was then developed for transferring predicted part forms from the finite element outputs to a digital manufacturing platform for the purpose of virtual assembly validation using more realistic part geometry. Ultimately, the outcomes from this work can be used to inform process condition choices, material configuration and tool design, so that the dimensional gap between ‘as-designed’ and ‘as-manufactured’ part forms can be reduced in the virtual environment.
For precision machining of large-sized optical elements, more attention is being paid to the ground surface quality, the processing costs and the machining efficiency. Besides the commonly used fine-grained diamond wheels, the coarse-grained diamond wheel is now also expected to be a promising tool with lower wheel wear rate and higher efficiency. However, conditioning of this kind of wheel is always a difficult issue to deal with. In this article, the efficient conditioning of the electroplated diamond wheel and precision grinding of BK7 glasses were investigated. Through the single diamond grit wear simulation, D3 steel was chosen as the conditioning tool. The worn diamond abrasive morphology and Raman spectroscopy analysis revealed the conditioning mechanism. Under different conditioning stages, the BK7 glasses were correspondingly ground exhibiting different surface integrity and grinding forces. The experimental results indicated that the wheel’s run-out error could be rapidly reduced to 5.8 µm because of the blend graphitization, passivation, diffusion and microcrushing of the diamond abrasives. The precision ground BK7 glasses could achieve a surface roughness of Ra < 20 nm and a subsurface crack depth around 2 µm, illustrating that the electroplated coarse-grained diamond wheel could be an alternative for precision grinding large-sized optical elements in terms of high accuracy, cost-effectiveness and high efficiency.
Disassembly issues are important in the sustainable manufacturing field. One of them is influence factor analysis and time prediction of product disassembly. To deal with such issue, taking the bolt as a removal object, this work designs its removal experiment considering some factors influencing its removal process. Moreover, factor analysis and ranking on removal time are performed by a grey relational analysis method. In addition, based on the analysed and obtained main factors on removal time, its prediction models are established by multiple linear regressions, artificial neural networks and optimized artificial neural networks based on genetic algorithm methods. A numerical example is given to illustrate the proposed models and the effectiveness of the proposed methods.
In this work, an analytical model for transient temperature distribution during submerged arc welding for joining two steel plates is presented. The conservation of energy equation is used to represent the thermal behaviour of the submerged arc welding process. A three-dimensional double-paraboloid shape for volumetric heat source with Gaussian distribution is considered for electric arc during welding, and a parabolic-shaped cross section for the weld pool is considered. A set of experiments is conducted to determine the geometric parameters. The final analytical solution considers effect of the electric arc, convective heat transfer from the exposed surface and heat of molten electrode material. Subsequently, the prediction is compared with experimentally predicted temperatures where a good agreement is found.
In production market, the decision-making patterns of firms producing a homogeneous kind of products are different. Some are under the control of a dominant firm called centralized pattern. In this case, there is only one decision maker who takes charge of all the firms and attempts to maximize the total utility of the system. Another is decentralized pattern, in which firms plan by themselves. In reality, there always exists a third pattern, where the centralized pattern and decentralized pattern firms are in the same market. This article deals with the last case and studies the effects of decentralized pattern firms’ decisions on centralized pattern firms in the same market, which is described as a Stackelberg game. It is supposed that centralized pattern firms are the leaders who affect the whole market by adjusting the production of each firm. Decentralized pattern firms are the followers who determine their productions in a manner of competitive equilibrium against the given centralized firm’s strategy. This game in this article is formulated as a bilevel programming model. Solution algorithm based on the sensitivity analysis is adopted to solve the model, and a numerical example is given to illustrate the model and algorithm.
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Design of Experiments (DoE) is a powerful technique for process optimization that has been widely deployed in almost all types of manufacturing processes and is used extensively in product and process design and development. There have not been as many efforts to apply powerful quality improvement techniques such as DoE to improve non-manufacturing processes. Factor levels often involve changing the way people work and so have to be handled carefully. It is even more important to get everyone working as a team. This paper explores the benefits and challenges in the application of DoE in non-manufacturing contexts. The viewpoints regarding the benefits and challenges of DoE in the non-manufacturing arena are gathered from a number of leading academics and practitioners in the field. The paper also makes an attempt to demystify the fact that DoE is not just applicable to manufacturing industries; rather it is equally applicable to non-manufacturing processes within manufacturing companies. The last part of the paper illustrates some case examples showing the power of the technique in non-manufacturing environments.
In this study, wrinkling failure in conventional spinning of a cylindrical cup has been investigated by using both finite element (FE) analysis and experimental methods. FE simulation models of a spinning experiment have been developed using the explicit finite element solution method provided by the software Abaqus. The severity of wrinkles is quantified by calculating the standard deviation of the radial coordinates of element nodes on the edge of the workpiece obtained from the FE models. The results show that the severity of wrinkles tends to increase when increasing the roller feed ratio. A forming limit study for wrinkling has been carried out and shows that there is a feed ratio limit beyond which the wrinkling failure will take place. Provided that the feed ratio is kept below this limit, the wrinkling failure can be prevented. It is believed that high compressive tangential stresses in the local forming zone are the causes of the wrinkling failure. Furthermore, the computational performance of the solid and shell elements in simulating the spinning process are examined and the tool forces obtained from wrinkling and wrinkle-free models are compared. Finally, the effects of the feed ratio on variations of the wall thickness of the spun cylindrical cup are investigated.
It is usually hard to obtain a good surface quality of carbon/carbon (C/C) composite by turning due to its non-homogeneity and anisotropy. Contrasting experiments of ultrasonic assisted turning (UAT) and common turning (CT) of the C/C composite were carried out using a polycrystalline diamond tool. The cylindrical surface of the turning was classified into four typical types based on different fibre orientations. The influence of fibre distribution characteristics on surface roughness was analysed by measuring and comparing the roughness of these surfaces, and an evaluation method of surface quality for the C/C composite after turning was established. The results of UAT experiments on the C/C composite show that UAT could effectively reduce the machining defect. The roughness of typical surfaces 1 and 2 machined using UAT was about 20 per cent lower than that using CT.
This paper reports an investigation of digital filtering of areal stratified surface textures. The Gaussian robust filtering technique was established, several typical robust weight functions were adopted and the valley suppression Rk filter of surface topography was also included. The results for areal surface topographies of symmetric ordinate distribution filtering were analysed and compared with those obtained after using the Gaussian regression filter. In these cases the waviness and roughness parameters after using Gaussian and other filters should be similar. The computer-generated areal surfaces that had triangular scratches and measured stratified surfaces were also subjected to filtering. The surface roughness distortion and computation time were compared. Based on the comparison results, some digital filters are recommended.
Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company's Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area.
Relative colour comparisons were performed using digital imaging techniques and analysis. A statistical method was used to quantify how well a test colour matched a colour standard. Colour histogram comparisons were performed by incorporating a combination of control limits (based on prediction intervals) and threshold limits that were calculated for each curve set. Test colours were imaged and compared to colour standards by calculating the per cent match for each of the RGB curves. Colours that did not show a per cent match of 60 per cent or greater in all three colour curves were considered failures. Some colour families, e.g. reds, required larger control limits to account for colour variability.