GRA in Combination with PCA for Multi-response End Milling Process Optimization

Abstract

In the present investigation of the project is to optimization of the end milling process parameters to provide a good surface finish. The Grey Relational Analysis (GRA) with Principal Component Analysis (PCA) to predicting the process performance of Surface Roughness (SR). The surface roughness Ra, Rq, Rz and Rsm is a chosen in process performance and speed, feed and depth of cut is machining parameters are chosen in this work. The L25 orthogonal array has been applied. Correlated with responses have been transmuted into uncorrelated or independent quality called Principal Component Analysis. The PCA having the highest accountability proportion is considered has the objective functions for multiple optimizations. Grey relational analysis is applied, and optimal values are calculated. The result shows speed 1000 rpm, the feed is 160 mm/min, and depth of cut 1 mm is the optimal results are identified.