Multi-response optimisation and performance evaluation of Inconel 625 superalloy machining under cryogenic cooling environment

Abstract

ABSTRACT The conventional machining of the widely used nickel-based superalloy Inconel 625 is challenging since it exhibits high strength at elevated temperatures. Cryogenic machining is an effective cooling technique to extract the heat developed during machining and enhance the machining performance of superalloys by eliminating the high-temperature related machining obstacles. The maximum machining performance of cryogenic machining can be achieved by optimising the input parameters considered for the study. This work attempts to improve the cryogenic machining performance of Inconel 625 using grey relational analysis. Multiple responses that are having the most significance on the performance of the machining such as main cutting force, tool wear and surface roughness were considered to optimise the process. The experiments were designed on the basis of the orthogonal array. Taguchi’s L9 design with three levels of cutting speed, feed and depth of cut was considered for conducting the experiments. A cutting speed of 60 m/min, feed of 0.05 mm/rev and depth of cut of 0.2 mm were obtained as the optimal parameters. The analysis of modes of wear and morphology of chips was also conducted using SEM imaging to understand the wear mechanisms and machining performance at the optimal level under cryogenic cooling.