Multi-objective Optimization of Wire Electric Discharge Machining of EN31 Tool Steel using Orthogonal array with Principal Component Analysis

Abstract

Recently mechanical industries, the demands for alloy steel materials having high hardness, toughness and wear resistance are increasing, having wide application in automobile products like bearing shafts, spindles etc is important for quality of cut. Keeping this view, a hybrid approach of Taguchi’s methodology (TM) and principle component analysis (PCA) has been applied for multi-objective optimization (MOO) of wire-cut EDM of EN31 steel. To achieve the better qualities using existing resources, the two quality characteristics, cutting speed and surface roughness have been considered for simultaneous optimization. The input parameter considered are Peak current (A), pulse-on time(B), pulse off time(C) and wire tension(D).Initially single-objective optimization has been performed using Taguchi’s methodology and then the S/N ratio obtained from TM have been further used in PCA for multi-objective optimization(MOO). The results of MOO include the prediction of optimum input parameter levels and their relative significance on multi quality characteristics. The resources at the predicted optimum parameter levels are in good agreement with the result of confirmation experiments for verification test..