A Two-Step Fuzzy MCDM Method for Implementation of Sustainable Precision Manufacturing: Evidence from China

Xiaowei Guan and Jun Zhao
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Xiaowei Guan: Guanghua Law School, Zhejiang University, Hangzhou 310008, China
Jun Zhao: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China

Sustainability, 2022, vol. 14, issue 13, 1-27

Abstract: Despite that products of precision manufacturing are widely used in many fields involving the national economy, precision manufacturing processes are more unfriendly to the environment, resources and social development than general manufacturing. Hence, the implementation of sustainable precision manufacturing (SPM) is of great strategic significance. There is no literature identifying and ranking the drivers of implementation of SPM and the impact on sustainability owing to the application of advanced manufacturing technologies in SPM has not been explored. To resolve these problems, drivers of SPM are identified based on combined support of prior studies and six groups of experts consisting of 71 individuals from six precision manufacturing enterprises. The drivers are calculated and ranked by a two-step fuzzy MCDM method which integrated the fuzzy AHP (fuzzy analytic hierarchy process) and fuzzy TOPSIS (fuzzy technique for order of preference by similarity to ideal solution) algorithms. The evaluation of drivers is based on the basic principles of sustainable development (environmental criterion, social criterion and economic criterion). The paper concludes that technological innovation, government support and current legislation are the most critical drivers during SPM implementation. Additionally, the result of sensitivity verification of the proposed method conducted proves the robustness and correctness of the algorithm and results.

Keywords: sustainable precision manufacturing; drivers; fuzzy TOPSIS; fuzzy AHP; fuzzy MCDM (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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