Multiobjective Optimization of Surface Integrity in Milling TB6 Alloy Based on Taguchi-Grey Relational Analysis

Abstract

This paper studied an effective method based on Taguchi's method with the grey relational analysis, focusing on the optimization of milling parameters on surface integrity in milling TB6 alloy. The grey relational grade that is derived from the grey relational analysis is mainly used to determine the optimum cutting process operations with multiple performance characteristics. Specifically, surface roughness (Ra), hardness, and residual stress were important characteristics in surface integrity of milling TB6 alloy. Based on the combination of these multiple performance characteristics, the feed per tooth, cutting speed, and depth of cut were optimized in this study. Additionally, the analysis of variance (ANOVA) was also applied to determine the most significant factor for the surface integrity of milling TB6 alloy according to the contribution of the ANOVA, and the most significant factor is the cutting speed in this paper. Based on the analysis, the experimental test results have been improved prominently through the grey relational analysis. Hence this method can be an effective approach to enhance the surface integrity of milling TB6 alloy.