Optimization of cutting parameters in CNC turning operation using Taguchi design of experiments

Abstract

Abstract Non-reinforced and reinforced Poly-Ether-Ether-Ketone (PEEK) plastics have excellent mechanical and thermal properties. Machining is an efficient process that can be used to manufacture specific mechanical parts made from PEEK composites. Researchers have focused on improving the performance of machining operations with the aim of minimizing costs and improving quality of manufactured products, in order to get the best surface roughness and the minimum cutting force. The parameters evaluated are the cutting speed, the depth of cut and the feed rate. In this paper, the effect of the mentioned parameters on surface roughness and cutting force, in dry turning of reinforced PEEK with 30% of carbon fibers (PEEK CF30) using TiN coated cutting tools, is analyzed through using robust design techniques such as Taguchi's design method, signal-to-noise (S/N) ratio and statistical analysis tools such as Pareto-ANOVA. The obtained results have shown that Taguchi method and Pareto ANOVA are suitable for optimizing the cutting parameters with the minimum possible number of experiments, and the optimized process parameters were determined for surface roughness and cutting force criteria.