Optimization of surface roughness on CNC milling machining using differential evolution (DE) method

Abstract

This paper presents the optimization of selected CNC milling parameters namely, spindle speed, feed rate and depth of cut on surface roughness of mild steel bar using High Speed Steel (HSS) insert tool. Performance of machining part and production cost were influenced by quality of the surface roughness, Ra. The optimum machining parameters setting is vital and critical. Thus, this study is designed to analyse and optimize the Ra using conventional method, Response Surface Method (RSM) and non-conventional method, Differential Evolution (DE). Firstly, the required experimental runs for data collection was designed by using Design of Expert software. Then, 36 experimental runs were conducted using CNC milling machine and the surface roughness were measured using surface roughness tester. Using the data collected a regression model was developed. Next, DE optimisation method using Matlab is carried out to find the optimum parameters value for minimum Ra. Finally, optimum machining parameters setting generated by RSM and DE, were validated and evaluated experimentally. DE found to be better in finding the optimum parameters value for lower Ra compared to RSM in this study.