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Research Article

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

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Pages 1303-1319 | Accepted 02 Mar 2023, Published online: 13 Mar 2023
 

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.

Acknowledgements

The authors acknowledge with gratitude the Central Facility for Materials and Manufacturing engineering (CFMM) and Central Instrumentation Facility (CIF) of Indian Institute of Technology Palakkad for providing the experimental and material characterisation facilities, and also thankful to Science and Engineering Research Board, Govt. of India for funding the project (Grant number: ECR/2017/000883).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the Science and Engineering Research Board [ECR/2017/000883]

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