Multi-objective optimisation for the micro-end milling process using principal component analysis technique

Nowadays, micro-machining processes are playing an important role because of the technological developments in the MEMS, electrical, medical and aerospace industries. In this research work, the principal component analysis (PCA) technique is used to examine and explains the influences of three process parameters (spindle speed, feed rate and depth of cut) on the output responses such as MRR and Ra in micro-end milling process. Also this approach is used for the optimisation of multiple responses in micro-end milling operation to achieve maximum metal removal rate (MRR) and minimum surface roughness (Ra). Further, the optimised machining parameters were determined considering the multiple response objective using multiple response performance index value. The predicted value of multiple response performance index (Z) is 0.6412 which is calculated by using additive model. The measured value of multiple response performance index is 0.707, which shows good prediction accuracy. From the experimental result, it was concluded that, the PCA technique is suitable for the optimisation of multi-response problem.