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Optimization of green machining processes using grey-based multi-criteria decision making methods: a comparative analysis

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Abstract

Green machining processes, which are essential for sustainable manufacturing practices, require minimization of energy consumption while maintaining desirable product quality and less perilous working environment. In this paper, the applications of three multi-criteria decision making (MCDM) techniques integrated with grey system theory are proposed for solving the parametric optimization problems of two green machining processes. Grey step-wise weight assessment ratio analysis (G-SWARA) method is first employed to compute the relative importance of the responses based on varying opinions of three decision makers, followed by the application of three G-MCDM approaches, i.e. measurement of alternatives and ranking according to compromise solution (MARCOS), multi-attributive border approximation area comparison (MABAC) and multi-attributive ideal-real comparative analysis (MAIRCA) to search out the optimal combinations of input parameters for a green milling and a green turning process. The results derived from both the illustrative examples prove that G-SWARA approach can subjectively rate the considered responses depending on the opinions and requirements of the stakeholders (machinist, process engineer or end user), while the G-MCDM approaches can effectively solve the parametric optimization problems of the green machining processes providing results comparable to real-time machining requirements.

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Authors and Affiliations

  1. Production Engineering Department, Jadavpur University, Kolkata, West Bengal, India

    Srinjoy Chatterjee & Shankar Chakraborty

  2. Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Rangpo, Majitar, Sikkim, India

    Partha Protim Das

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  1. Srinjoy Chatterjee
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Correspondence to Shankar Chakraborty.

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Chatterjee, S., Das, P.P. & Chakraborty, S. Optimization of green machining processes using grey-based multi-criteria decision making methods: a comparative analysis. Int J Interact Des Manuf 18, 33–53 (2024). https://doi.org/10.1007/s12008-023-01403-8

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