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Design of a Reverse Logistics System with Internet of Things for Service Parts Management

Author

Listed:
  • Daniel Y. Mo

    (Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong, China)

  • Chris Y. T. Ma

    (Department of Computing, The Hang Seng University of Hong Kong, Hong Kong, China)

  • Danny C. K. Ho

    (Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong, China)

  • Yue Wang

    (Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong, China)

Abstract

Despite that reverse logistics of service parts enables the reuse of failed components to achieve greater environmental and economic benefits, the research and successful business cases are inadequate. This study designs a novel reverse logistics system that applies the Internet of Things (IoT) and business intelligence to streamline the reverse logistics process by identifying the appropriate components for sustainable operations of component reuse. Furthermore, an inventory classification scheme and an analytical model are developed to identify the failed components for refurbishment by considering return quantity of the failed component, repair rate of the failed component in the repairing center, reusable rate of refurbished parts, corresponding costs, and the benefit of refurbished parts. Moreover, a mobile application powered by the IoT technology is developed to streamline the process flow and avoid collection of fake components. Lastly, a case study of an electronic product company is conducted, and it is concluded that the proposed approach enabled the company to facilitate the reuse of components and achieve the benefit of cost saving. The results of this study demonstrate the importance of a reverse logistics system for companies to sustain after-market service operations.

Suggested Citation

  • Daniel Y. Mo & Chris Y. T. Ma & Danny C. K. Ho & Yue Wang, 2022. "Design of a Reverse Logistics System with Internet of Things for Service Parts Management," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12013-:d:922648
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    References listed on IDEAS

    as
    1. Nima Kazemi & Nikunja Mohan Modak & Kannan Govindan, 2019. "A review of reverse logistics and closed loop supply chain management studies published in IJPR: a bibliometric and content analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4937-4960, August.
    2. Y. P. Tsang & C. H. Wu & H. Y. Lam & K. L. Choy & G. T. S. Ho, 2021. "Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1534-1556, March.
    3. Luis Isasi-Sanchez & Jesus Morcillo-Bellido & Jose Ignacio Ortiz-Gonzalez & Alfonso Duran-Heras, 2020. "Synergic Sustainability Implications of Additive Manufacturing in Automotive Spare Parts: A Case Analysis," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    4. Daniel Y. Mo & Yue Wang & Danny C. K. Ho & K. H. Leung, 2022. "Redeploying excess inventories with lateral and reverse transshipments," International Journal of Production Research, Taylor & Francis Journals, vol. 60(10), pages 3031-3046, May.
    5. Daniel Y. Mo & Yue Wang & Lawrence C. Leung & Mitchell M. Tseng, 2020. "Optimal service parts contract with multiple response times and on-site spare parts," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 3049-3065, May.
    6. Syntetos, A.A. & Babai, M.Z. & Davies, J. & Stephenson, D., 2010. "Forecasting and stock control: A study in a wholesaling context," International Journal of Production Economics, Elsevier, vol. 127(1), pages 103-111, September.
    7. Atanu Sengupta & Sanjoy De, 2020. "Review of Literature," India Studies in Business and Economics, in: Assessing Performance of Banks in India Fifty Years After Nationalization, chapter 0, pages 15-30, Springer.
    8. Murthy, D. N. P. & Solem, O. & Roren, T., 2004. "Product warranty logistics: Issues and challenges," European Journal of Operational Research, Elsevier, vol. 156(1), pages 110-126, July.
    9. Yasaman Mashayekhy & Amir Babaei & Xue-Ming Yuan & Anrong Xue, 2022. "Impact of Internet of Things (IoT) on Inventory Management: A Literature Survey," Logistics, MDPI, vol. 6(2), pages 1-19, May.
    10. Wenyuan Wang & Daniel Y. Mo & Yue Wang & Mitchell M. Tseng, 2019. "Assessing the cost structure of component reuse in a product family for remanufacturing," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 575-587, February.
    11. Wang, Wenyuan & Wang, Yue & Mo, Daniel & Tseng, Mitchell M., 2017. "Managing component reuse in remanufacturing under product diffusion dynamics," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 551-560.
    12. Shuai Zhang & Kai Huang & Yufei Yuan, 2021. "Spare Parts Inventory Management: A Literature Review," Sustainability, MDPI, vol. 13(5), pages 1-23, February.
    13. A H C Eaves & B G Kingsman, 2004. "Forecasting for the ordering and stock-holding of spare parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 431-437, April.
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