<![CDATA[This paper presents the optimization of the side milling process of Al 6061, with multiple performance characteristics based on the orthogonal array with Taguchi method and Weighted Principal Component Analysis (WPCA). The experimental studies were conducted under varying side milling process variables, i.e., main axis of rotation , feed rate and radial depth of cut. The optimized multiple performance characteristics were surface roughness and tool wear. Weighted Principal Component Analysis (WPCA) has been applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Based on individual principal components a Multi-Response Performance Index (MPI) has been introduced to derive an equivalent single objective function which has been optimized (maximized) using Taguchi method. Since main axis of rotation, feed rate and radial depth of cut had three levels, the experiment design used L9 orthogonal array with replication. The quality characteristics of surface roughness and tool wear were smaller-is-better. Optimal result has been verified by confirmatory test. Experimental results have shown that machining performance in the side milling process can be improved effectively through this method. The side milling process variables which significantly affected surface roughness and tool wear are main axis of rotation and feed rate.]]>
Copyrights © 2017
