Optimization of CNC machining parameters to improve surface roughness quality of the AL6061 material using the Taguchi method

Abstract

Surface quality is an important variable of a milling machining process. Therefore, choosing the best machining parameters is very important to arrange so that the best surface quality can be obtained. The purpose of this research is to optimize machining parameters by using surface roughness as a performance indicator variable. This research was carried out by making 9 surface roughness test specimens through a facing process on a TU-3A CNC milling machine. Each test specimen is made with a different level of machining parameters. Machining parameters used in this research are spindle speed, feed rate, and depth of cut. Surface roughness values obtained from 9 test specimens were analyzed using the Taguchi method, signal-to- noise ratio, and ANOVA. The Taguchi approach is also used to predict the best machining parameter configurations. The results of the signal-to-noise ratio analysis show that the surface quality is affected by spindle speed, depth of cut and feed rate, respectively. The results of measurements on 9 test specimens showed the best roughness values were 0.275µm. While the results of the Taguchi analysis show that the optimal surface roughness value can be obtained at 0.267µm for machining conditions with the parameters spindle speed 1100 rpm, feed rate 85 mm/min and depth of cut 0.25 mm. Furthermore, analysis of variance (ANOVA) yielded contribution values from spindle speed, feed rate and depth of cut to the surface roughness values of 51.80%, 36.88% and 10.72%, respectively