Optimization of tool wear, surface roughness and material removal rate in the milling process of al 6061 using Taguchi and weighted principal component analysis (WPCA)

In the metal cutting industry, end milling has an important role in cutting metal to obtain the various required shapes and size. This study takes Al 6061 as working material and investigates three performance characteristics, i.e., tool wear (VB), surface roughness (Ra) and material removal rate (MRR), with Taguchi method and WPCA for determining the optimal parameters in the end milling process. The performance characteristic of MRR is larger-the-better while VB and Ra are having smaller-the-better performance characteristic. Based on Taguchi method, an L18 mixedorthogonal array was chosen for the experiments. The optimization was conducted by using weighted principal component analysis (WPCA). As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. The most significant machining parameters which affected the multiple performance characteristics were type of milling operation, spindle speed, feed rate and depth of cut. Experimental result have also shown that machining performance characteristics of end milling process can improved effectively through the combination of Taguchi method and WPCA.