Smart recovery decision-making of used industrial equipment for sustainable manufacturing: belt lifter case study

Kai Meng (), Xiaoming Qian (), Peihuang Lou () and Jiong Zhang ()
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Kai Meng: Massachusetts Institute of Technology
Xiaoming Qian: Nanjing University of Aeronautics and Astronautics
Peihuang Lou: Nanjing University of Aeronautics and Astronautics
Jiong Zhang: Miracle Automation Engineering Co., LTD

Journal of Intelligent Manufacturing, 2020, vol. 31, issue 1, No 10, 183-197

Abstract: Abstract End-of-Life (EOL) product recovery is proved to be an attractive way to achieve sustainable manufacturing while extending the producer’s responsibility to closed-loop product service. However, it is still a challenge to provide flexible and smart recovery plans for industrial equipment at different periods of product service. In this paper, we investigate the smart recovery decision-making problem. We propose a system framework for the implementation of smart EOL management based on product condition monitoring. Different product-level EOL business strategies and component-level recovery options are suggested in this recovery decision support system. Then, multi-objective optimization models are formulated to identify the age-dependent recovery roadmap that best matches the product condition and meets the business goals. In order to achieve environmentally friendly recovery, both recovery profits and energy performances are optimized in our models. We conduct a case study of belt lifter used in the automobile assembly line. The Non-dominated Sorting Genetic Algorithm II is used to solve the proposed model. Numerical experiments validate our models and provide practical insights into flexible recovery business.

Keywords: Sustainable manufacturing; Product recovery; End-of-life management; Smart manufacturing; Multi-objective optimization (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10845-018-1439-2

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