Comparing Taguchi Method and RSM for Optimizing Flank Wear and Surface Roughness During Hard Turning of AISI D3 Steel

Abstract

The present work attempts to investigate tool wear (flank wear) and surface roughness (Ra) during finish hard turning of AISI D3 steel (58HRC) with coated carbide (TiSiN–TiAlN PVD coated) cutting tool. Taguchi L9 (3)3 orthogonal array has been applied for experimental design. Signal-to-noise (S/N) ratio (Lower the best) and analysis of variance (ANOVA) analyses were performed to identify significant parameters influencing tool wear and Ra. The cutting speed and feed were the most significant factor influencing tool wear (flank wear), and feed is the most significant factor influencing Ra. Mathematical models for both response parameters, i.e., tool wear and Ra were obtained through regression analysis. The confirmation experiments carried out at optimal combination of parameters given by Taguchi analysis predicted the response factors with less than 5 % error. In addition to this desirability function module, response surface methodology (RSM) was applied to arrive at the optimal setting of input parameters to minimize tool wear and Ra and to compare this with optimal setting of parameters given by Taguchi analysis. The optimization results provided by desirability function optimization is quite close to the optimal solutions provided by Taguchi analysis.