Multi-objective optimisation of cryogenic turning process using Taguchi-based grey relational analysis

Abstract

Cryogenic machining is a sustainable manufacturing approach; it eliminates coolant disposal cost, health problems compared to the conventional flood cooling. The present study investigates the multiple response optimisation of turning process while machining AISI 17-4 PH stainless steel under the cryogenic environment (jetting of liquid nitrogen at -196 C at the rake face of the tool) by using Taguchi-based grey relational analysis. The optimum levels of the machining parameters are cutting speed at 120.89 m/min, feed rate at 0.048 mm/rev, depth of cut 0.4 mm and physical vapour deposition (PVD) AlTiN coated tungsten carbide (WC). Taguchi-based grey relational analysis method reduced the cutting forces by 7.75%, improved the surface finish by 55.87%, and increased the material removal rate (MRR) by 154.76% and 25% increased the tool flank wear in cryogenic turning process. From the analysis of variance, it was identified that feed rate is the most influenced process parameter on turning performance characteristics. Copyright 2017 Inderscience Enterprises Ltd.