Decision-making method of heavy-duty machine tool remanufacturing based on AHP-entropy weight and extension theory

Yanbin Du, Yashi Zheng, Guoao Wu, Ying Tang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Heavy-duty machine tools are mostly used in bottleneck processes of manufacturing companies, which have high value-added, high technical content, and large remanufacturing value. The various alternative solutions directly affect the implementation of heavy-duty machine tool remanufacturing as well as its benefits. However, there is currently no scientific and reasonable quantitative method to compare various options and determine the optimal solution. This paper aims to propose a decision-making method of heavy-duty machine tool remanufacturing based on the AHP-entropy weight and extension theory. Firstly, an evaluation criteria system of heavy-duty machine tool remanufacturing is established, covering economic criteria (including remanufacturing cost and remanufacturing time) and technical performance criteria (including accuracy, reliability, processing efficiency, processing range, and ergonomics). Secondly, the decision-making model is presented to determine the optimal alternative solution for heavy-duty machine tool remanufacturing based on extension theory, in which weight for each evaluation criterion is defined by a method of AHP-entropy weight. Finally, combined with the remanufacturing of a heavy-duty horizontal lathe, the proposed decision-making method is verified and analyzed. The results show that the alternative for heavy-duty machine tool remanufacturing determined by this method can obtain better comprehensive benefits and reduce the potential risk of remanufacturing for various stakeholders.

Original languageEnglish (US)
Article number119607
JournalJournal of Cleaner Production
Volume252
DOIs
StatePublished - Apr 10 2020

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All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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