Experimental investigation and optimization of sustainable performance measures during wire-cut EDM of Ti-6Al-4V alloy employing preference-based TLBO algorithm

Abstract

ABSTRACT This article evaluates performance of wire-cut electrical discharge machining technique on Ti6Al4V alloy. Taguchi L16 experimental design is employed considering four cutting variables each at four different levels. Two sustainable performance measures viz., material removal rate (MRR) and surface roughness (SR) were investigated. Multiple response optimization (MRR and SR) was performed employing teaching-learning-based optimization (TLBO) using various weight combinations. A set of optimal solutions close to Pareto optimal fronts were obtained for each pair of weights, which helps decision maker to select appropriate cutting conditions obtain desired MRR and SR. The proposed preference-based multi objective optimization using TLBO (PBMOO-TLBO) methodology exhibited faster convergence and obtained optimal solutions in less than 20 iterations. Optimization result showed 40.51% improvement in MRR and SR recorded to decrease by 15.66% with highest preference as compared to equal weightage assigned. Result of optimization obtained in the present study can be used to produce Ti/6Al/4 V alloy components having desired SR with higher MRR. Experimental study of responses and surface morphology study are also presented.