Optimal process parameters for minimizing the surface roughness in CNC lathe machining of Co28Cr6Mo medical alloy using differential evolution

Abstract

This study is conducted to observe the optimal effect of rotational speed, feed rate, depth of cut, and tool tip radius on the surface roughness of a material. In the machining processes, surface roughness value should be made as low as possible and is determined by the value of the optimal process parameters. Currently, the application of differential evolution (DE) optimization technique in optimizing the process parameters for achieving minimum surface roughness, especially in CNC lathe machining of Co28Cr6Mo medical alloy, is still not given any consideration by the researcher. Therefore, in this study, a new approach of CNC lathe parameters optimization using DE algorithm is introduced. At first, a regression model is developed from the actual machining data provided by Asilturk, Neseli, and Ince [1]. The regression model of the surface roughness is formulated as a fitness function for DE algorithm. The results of this study have proven that the DE optimization technique is able to estimate the optimal process parameters that yield minimum surface roughness. The application of DE as a solution approach in process parameter optimization has significantly improve the surface roughness (Ra) where the Ra value is reduced by 81, 72, and 30% when compared to the experiments, regression modeling, and response surface methodology (RSM) respectively.