Principal Component Analysis of Correlated WEDM Performance Characteristics during Machining ZC63/SiC_P MMCs

Abstract

The present investigation proposes the optimization of the wire electrical discharge machining process for machining ZC63/SiC_P metal matrix composite. SiC particulate size and its percentage with the matrix are considered as the process variables along with the most significant WEDM variables such as pulse-on time, pulse-off time and wire tension. In view of quality cut, surface roughness, metal removal rate and kerf are considered as the process responses. Since, these responses are correlated with each other and they need to be optimized simultaneously. Therefore, the problem is treated as multi-response optimization problem. Principal component analysis (PCA) has been implemented to convert the multi-objective optimization problem in to single objective optimization problem by converting the multiple correlated responses in to the total quality index. Taguchi's robust optimization technique has been adopted to derive the set optimal process parameters which maximize the total quality index. The derived optimal process responses are confirmed with the experimental validation tests. ANOVA is conducted find the importance of the chosen process variables on the overall quality of the machined component. The practical possibility of the obtained optimal process performance is observed using SEM studies.