Multi-objective optimization of high-speed turning parameters for hardened AISI S7 tool steel using grey relational analysis

Abstract

Nowadays, die manufacturing industries prefer eco-friendly machining, i.e., high-speed turning for hardened AISI S7 tool steel followed by the conventional grinding process. The effectiveness of this eco-friendly turning depends on selection of appropriate process parameters, which decides the surface integrity of machined components. Hence, the first objective of present research work is to optimize the turning parameters for lower cutting force, machining temperature, surface roughness and higher material removal rate simultaneously using grey relational analysis (GRA). ANOVA utilized to identify the significant effect of each turning parameter on the response variables. Secondly, the effects of turning parameters such as tool nose radius (Rn), cutting speed (Vc), feed rate (Vf) and depth of cut (dc) on tool wear and finished surface topography were studied through scanning electron microscopy (SEM) and atomic force microscope (AFM). Optimal turning parameters for multi-performance responses were Rn: 1.2 mm, Vc: 450 m/min, Vf: 0.05 mm/rev and dc: 0.2 mm. The confirmation test was conducted on the optimal parameter level. According to ANOVA, depth of cut was the major influencing factor on all response variables. AFM and SEM micrograph indicated that excellent surface quality with lower surface roughness (Sa: 64.21 nm and Sq: 90.34 nm) was observed at higher cutting speed. Flank and crater wear were observed in cutting tool faces owing to thermo-mechanical loading. Different wear mechanisms like abrasion, adhesion, built-up edge formation and chipping hammering were found in the alumina-mixed ceramic insert at higher cutting speed and depth of cut.