2014 : 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)

Ir. Bobby Oedy Pramoedyo S. MSc., Ph.D.
Bambang Pramujati ST, MSc.Eng, Ph.D


Abstract

Article PreviewArticle PreviewIn 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, ie, 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 L 18 mixed-orthogonal 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 …