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Internet of Things (IoT) driven kanban system for reverse logistics: solid waste collection

Author

Listed:
  • M. Thürer

    (Jinan University (Zhuhai Campus)
    Jinan University (Zhuhai Campus))

  • Y. H. Pan

    (Jinan University (Zhuhai Campus)
    Guangdong University of Technology)

  • T. Qu

    (Jinan University (Zhuhai Campus)
    Jinan University (Zhuhai Campus))

  • H. Luo

    (Jinan University (Zhuhai Campus)
    Jinan University (Zhuhai Campus))

  • C. D. Li

    (Jinan University (Zhuhai Campus))

  • G. Q. Huang

    (Jinan University (Zhuhai Campus)
    The University of Hong Kong)

Abstract

Increasing consumer awareness and soaring prices for raw material make reverse logistics an ever more important aspect of the product life cycle. However, most research focuses on the remanufacturing and recycling process leaving the actual tasks of waste collection behind. Moreover, existing research on waste collection typically assumes the problem to be deterministic, neglecting its stochastic nature. This study first diagnoses the solid waste collection problem; it is classified as an inventory control problem with confluent material flows and stochastic demand. A type of control system designed for this kind of problem is the kanban system. In response, the applicability of a kanban system for solid waste collection is discussed. While kanbans are a suitable mean to signal time and quantity of waste collection, the large quantity of collection points and geographical distances involved hinder its direct application. How the kanban system can be driven by the Internet of Things (IoT) was consequently the second objective of this study. Using a framework of an IoT driven production logistics system the control structure of the original kanban system has been analyzed. Out of this analysis the architecture of an IoT driven kanban system for solid waste collection is proposed.

Suggested Citation

  • M. Thürer & Y. H. Pan & T. Qu & H. Luo & C. D. Li & G. Q. Huang, 2019. "Internet of Things (IoT) driven kanban system for reverse logistics: solid waste collection," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2621-2630, October.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:7:d:10.1007_s10845-016-1278-y
    DOI: 10.1007/s10845-016-1278-y
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    References listed on IDEAS

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    Cited by:

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    2. Feng, Yunting & Lai, Kee-hung & Zhu, Qinghua, 2022. "Green supply chain innovation: Emergence, adoption, and challenges," International Journal of Production Economics, Elsevier, vol. 248(C).
    3. Mladen Krstić & Giulio Paolo Agnusdei & Pier Paolo Miglietta & Snežana Tadić & Violeta Roso, 2022. "Applicability of Industry 4.0 Technologies in the Reverse Logistics: A Circular Economy Approach Based on COmprehensive Distance Based RAnking (COBRA) Method," Sustainability, MDPI, vol. 14(9), pages 1-30, May.
    4. Mohammed Alkahtani & Aiman Ziout & Bashir Salah & Moath Alatefi & Abd Elatty E. Abd Elgawad & Ahmed Badwelan & Umar Syarif, 2021. "An Insight into Reverse Logistics with a Focus on Collection Systems," Sustainability, MDPI, vol. 13(2), pages 1-22, January.
    5. Ziwen Zhang, 2022. "Internet of Things-Enabled Logistic Warehouse Scheduling Management With Human Machine Assistance," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(4), pages 1-17, October.
    6. Bueno, Adauto & Goyannes Gusmão Caiado, Rodrigo & Guedes de Oliveira, Thaís Lopes & Scavarda, Luiz Felipe & Filho, Moacir Godinho & Tortorella, Guilherme Luz, 2023. "Lean 4.0 implementation framework: Proposition using a multi-method research approach," International Journal of Production Economics, Elsevier, vol. 264(C).
    7. Liang Hou & Roger J. Jiao, 2020. "Data-informed inverse design by product usage information: a review, framework and outlook," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 529-552, March.

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