Smart recovery decision-making of used industrial equipment for sustainable manufacturing: belt lifter case study
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10845_2018_1439_ReferencePDF.pdf
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Author(s)
Meng, Kai
Qian, Xiaoming
Lou, Peihuang
Zhang, Jiong
Date Issued
July 31, 2018
Publisher
Springer US
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s10845-018-1439-2
