Multi response optimization of turning operation with self-propelled rotary tool

Abstract

The purpose of the study is to determine the cutting performance of self-propelled rotary tool (SPRT) in the turning operation of hardened EN24 steel by optimizing the cutting conditions. Parameters such as horizontal inclination angle of the SPRT, depth of cut, feed rate and spindle speed were chosen while two conflicting factors; surface roughness (Ra) and metal removal rate (rMMR) were decided as performance criteria. Regression model was used to determine the quantitative relationships between the process variables in terms of performance parameters. Then, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Non-dominated Sorting Genetic Algorithm-II (NSGA-II)-TOPSIS Hybrid Model and Goal Programming methods were employed to obtain the optimum conditions. In the analyses, optimization was determined by minimizing the Ra and maximizing the rMMR. Consequently, Goal Programming produced better results among the applied models. Optimum cutting conditions help operators and engineers to make decisions in the turning operations.