OPTIMIZATION OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESS USING TAGUCHI BASED MULTI-CRITERIA DECISION MAKING (MCDM) TECHNIQUE FOR TURNING OF AL-6082

Abstract

The current work discusses the experimental investigation for the optimization of cutting parameters for turning process. The effect of process parameters-cutting speed, feed rate and depth of cut investigated against the response variables-Material Removal Rate (MRR) and Surface Roughness (Ra) for aluminium-6082 material. Each experiment is performed for two replications to minimize error and contribution of noise factors. Signal to Noise ratio (SNR) and mean values are computed to identify optimum levels of process parameters. Analysis of Variance (ANOVA) and F-test performed at 95% confidence interval. Regression analysis shows the high level of correlation for MRR and moderate correlation for Ra. TOPSIS and GRA are used to evaluate the effectiveness of the optimization process during turning operation for AL-6082.

Keywords

• turning; material removal rate
• surface roughness
• anova
• topsis
• grey relation analysis