Investigation of surface roughness in face milling processes

Abstract

This study aims to investigate the effects of dry, minimum quantity lubrication (MQL), and nanofluid cutting conditions on surface roughness (Ra) and material removal rate (MRR) for Al6082-T6. Three controllable factors, namely, feed rate (Fr), spindle speed (Vs), and depth of cut (Dc) are studied at three levels using Taguchi method. Single-response optimization is conducted using S/N ratio and contour plots. Empirical models of Ra and MRR for all cutting conditions are developed, and analysis of variance (ANOVA) is used to measure the adequacy of these models. Experimental results reveal that 26~30% improvement in Ra could be observed when experimental setup shifted from dry to MQL, and 13~16% improvement is recorded when further shifted to nanofluid cutting condition. No remarkable effect of cutting conditions (dry, MQL, and nanofluid) is observed on MRR. Additionally, Vs is observed insignificant for MRR in all cutting conditions. The appropriate cutting conditions and optimum values of input variables are proposed to the practitioners for industrial machining and production when contemplating face milling processes.