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. © © 2017 Inderscience Enterprises Ltd.