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A novel hybrid approach GREG-fuzzy-GA for minimizing work piece temperature during 2.5D milling of Inconel625 super alloy

Satish Kumar (Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India)
Arun Gupta (Department of Mechanical Engineering, Maharishi Markandeshwar Group of Institutions, Ambala, India)
Anish Kumar (Department of Mechanical Engineering, Maharishi Markandeshwar Group of Institutions, Ambala, India)
Pankaj Chandna (Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India)
Gian Bhushan (Department of Mechanical Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India)

World Journal of Engineering

ISSN: 1708-5284

Article publication date: 1 June 2023

Issue publication date: 26 April 2024

46

Abstract

Purpose

Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls.

Design/methodology/approach

Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization.

Findings

SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized.

Originality/value

The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

Keywords

Acknowledgements

Funding: There is no funding agency for this research work.

Declaration of conflicting interests: The author(s) declared that they have no potential conflicts of interest with respect to the research, authorship and publication of this article.

Citation

Kumar, S., Gupta, A., Kumar, A., Chandna, P. and Bhushan, G. (2024), "A novel hybrid approach GREG-fuzzy-GA for minimizing work piece temperature during 2.5D milling of Inconel625 super alloy", World Journal of Engineering, Vol. 21 No. 3, pp. 535-548. https://doi.org/10.1108/WJE-07-2022-0273

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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