Multicharacteristic optimisation of CNC turned parts using principal component analysis

Abstract

This paper optimises the multiple characteristics (tool life, cutting force, surface roughness and power consumption) in CNC turning of AISI P-20 tool steel using Principal Component Analysis (PCA). Five controllable factors of the turning process were studied at three levels each viz cutting speed, feed, depth of cut, nose radius and cutting environment. L27 Orthogonal array was used for conducting the experiments. The single response optimisation was conducted by Taguchi method. PCA was employed to correspond to multi response cases. The optimum combination of process factors based on first principal component was determined which was subsequently studied by extracting more then one principal component and integrating into comprehensive index. Finally, the Analysis of Variance (ANOVA) was used to find out the most influential CNC turned parameter for multiple response problems. © 2008, Inderscience Publishers.