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Quality-driven recovery decisions for used components in reverse logistics

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  • Kai Meng
  • Peihuang Lou
  • Xianghui Peng
  • Victor Prybutok

Abstract

Reverse logistics has emerged as a promising strategy for enhancing environmental sustainability through remanufacturing, reusing, or recycling used components. It is crucial to pursue quality-driven decision-making for component recovery because quality is a dominant factor for component salvage value and its recoverability. To maximise the profit from component recovery, a quality-driven decision model was proposed in this study. Remaining useful life (RUL) was utilised as a measure of quality in the proposed model, where conditional RUL distribution was predicted by utilising both the failure data and condition monitoring data based on a proportional hazard model. Under RUL uncertainty, an interval decision-making approach was developed to suggest recovery strategies for the decision-makers to identify a satisfactory solution according to their risk preferences. Compared to the existing approaches for quality-driven recovery decision-making based on RUL prediction, this work provides a more accurate and powerful approach to managing and mitigating decision risk. Numerical experiments demonstrated the effectiveness and superiority of the proposed model.

Suggested Citation

  • Kai Meng & Peihuang Lou & Xianghui Peng & Victor Prybutok, 2017. "Quality-driven recovery decisions for used components in reverse logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4712-4728, August.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:16:p:4712-4728
    DOI: 10.1080/00207543.2017.1287971
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    References listed on IDEAS

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    Cited by:

    1. Kai Meng & Xiaoming Qian & Peihuang Lou & Jiong Zhang, 2020. "Smart recovery decision-making of used industrial equipment for sustainable manufacturing: belt lifter case study," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 183-197, January.
    2. Yue Tan & Chunxiang Guo, 2019. "Research on Two-Way Logistics Operation with Uncertain Recycling Quality in Government Multi-Policy Environment," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    3. Dominik Zimon & Jonah Tyan & Robert Sroufe, 2019. "Implementing Sustainable Supply Chain Management: Reactive, Cooperative, and Dynamic Models," Sustainability, MDPI, vol. 11(24), pages 1-22, December.

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