Machine learning enabled CRITIC–CoCoSO optimization of PVA/CSP/AgNPs films for multifunctional packaging applications

Balasubramanian Karthekeyan Parrthipan, Balavairavan Balasubramanian, Mohammed Raffic Noor Mohamed, Pratheesh Krishnankutty, Senthamaraikannan Palanisamy, Sivarao Subramonian, Senthilkumar Manakavala perumal, Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Department of Aeronautical Engineering, Nehru Institute of Technology, Engineering Department, College of Engineering and Technology, University of Technology and Applied Sciences, Centre of Excellence-Advanced Materials Synthesis , Department of Mechanical Engineering, Alliance School of Applied Engineering, Alliance University, Sophisticated Testing and Instrumentation Centre , Alliance University, Faculty of Industrial and Manufacturing Technology and Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Department of Mechanical Engineering, SCAD College of Engineering and Technology

Journal of Thermoplastic Composite Materials

Published online on March 18, 2026

Abstract

Journal of Thermoplastic Composite Materials, Ahead of Print.
The current research has proposed an innovative methodology to enhance PVA/CSP/AgNPs hybrid biocomposite films by integrating the CRITIC and CoCoSo multi-criteria decision-making (MCDM) frameworks with machine learning techniques. Bio composite films can ...