A Comparison between different Optimization Techniques for CNC End Milling Process

Different kind of statistical optimization techniques are available for optimizing the different parameters of a CNC end milling process. In this paper a comparison is done between five different techniques such as principal components analysis, utility theory, Grey relational analysis, technique of order preference by similarity to ideal solution and their hybrid variants. The Taguchi optimization principle is common to all the methods which are presented in the paper. The experiments were carried out and the different response features such as surface roughness (Ra, Rz and Rq) and material removal rate (MRR) were measured and the different optimization techniques were applied. Three different surface roughness values are used for the analysis and they act as indices of surface quality whereas MRR acts as index of productivity. Hence the optimization is carried out such that the resulting optimized parameters will lead to a compromise between the productivity and the surface quality. The aim of the work is to carry out multi objective optimization on a single process and compare the results.