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Multi-objective optimization of wire electrical discharge machining process using evolutionary computation method: Effect of cutting variation

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Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Published online on

Abstract

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.