Original Article

Enhancing multi-response performance of AA2014 hybrid AMMC using TOPSIS algorithm on spark erosion machine

¹ Department of Mechanical Engineering, Annai College of Engineering and Technology, Thanjavur 612503, Tamil Nadu, Chennai, India
² Department of Mechanical Engineering, Mahendra Institute of Technology (Autonomous), Namakkal District 637503, Tamil Nadu, India
³ Department of Mechanical Engineering, SRM Institute of Science and Technology Tiruchirappalli, Tiruchirappalli 621 105, Tamil Nadu, India

*e-mail: selvalakshmanan86@gmail.com

Received: 6 January 2025
Accepted: 6 May 2025

Abstract

This research proposes WEDM machining parameter optimization of AA2014 Hybrid aluminium metal matrix composites (AMMC) by the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. The major machining responses optimized are Material Removal Rate (MRR), Surface Roughness (SR), and Tool Wear Rate (TWR). The optimization process resulted in a remarkable improvement, with the MRR of 22.5% being improved, the SR of 15.8% decreased, and the TWR of 17.3% decreased compared to un-optimized values. The findings depict higher productivity and accuracy that is needed in application in aerospace and biomedical engineering, among others, where AA2014 Hybrid AMMC is commonly used. The use of TOPSIS is apt because it is easy to process conflicting responses compared to other multi-response optimization methods such as Grey Relational Analysis (GRA) and Response Surface Methodology (RSM). Unlike GRA, where normalization is achieved in a sophisticated way, and RSM, which involves predictive modeling, TOPSIS can efficiently process closeness to an ideal solution and hence includes an ideal approach to multi-objective optimization. Also, the current investigation delivers valuable information regarding optimizing WEDM processes on AA2014 Hybrid AMMC and presents a viable solution to enhance machining performance, product quality, and tool life. The results possess important industrial values and make a precious contribution toward efficient utilization of AA2014 Hybrid AMMC in mission-critical applications.