Machinability analysis and hybrid optimization during wet turning of SS304 using coated tools

In this work, SS304 has been machined using tungsten carbide tool inserts coated with multilayer of TiN/ TiAlN under conventional wet cooling condition. Experiments have been conducted based on Taguchi robust technique with L9 orthogonal array. Effects of three important machining parameters cutting speed (CS), feed (F), and depth of cut (DC) on machinability aspects i.e. surface roughness (Ra) and material removal rate (MRR) have been investigated. Further, grey relational technique integrated with genetic algorithm (GA) was used for simultaneous optimization of MRR and Ra. It was observed that the optimized machining parameter setting for MRR and Ra is CS: 170 m/min; F: 0.2 mm/rev; and DC: 0.5 mm. The optimum values of MRR and Ra are 81.39 g/min and 3.14 mm respectively. (C) 2019 Elsevier Ltd. All rights reserved.