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Fostering the Reuse of Manufacturing Resources for Resilient and Sustainable Supply Chains

Author

Listed:
  • Alessia Napoleone

    (Department of Materials and Production, Aalborg University, Fibigerstraede 16, 9220 Aalborg, Denmark)

  • Alessandro Bruzzone

    (Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti, University of Genoa, Via Opera Pia 15, 16145 Genoa, Italy)

  • Ann-Louise Andersen

    (Department of Materials and Production, Aalborg University, Fibigerstraede 16, 9220 Aalborg, Denmark)

  • Thomas Ditlev Brunoe

    (Department of Materials and Production, Aalborg University, Fibigerstraede 16, 9220 Aalborg, Denmark)

Abstract

In the current context characterized by turbulent market conditions and the increasing relevance of sustainability requirements, reconfigurable manufacturing systems (RMSs) offer great potentialities for supply chains and networks. While plenty of contributions have addressed RMSs from a technological and system-specific perspective since the mid-1990s, the research interest for the strategic potentialities of RMSs at the supply chain level is recent and mainly related to building supply chains’ resilience and sustainability. Despite the interest, methods to support supply chains to strategically exploit RMSs are still missing, while being highly needed. In this paper, a method—consisting of an index to assess machines reusability and a mixed integer programming (MIP) algorithm—is provided to support the identification of reusable and reconfigurable machine candidates at the early stage of the strategic network design. The overall method allows machines to be compared based on their reusability and geographical locations. The application of the method, as well as an example referring to the production of emergency devices during the COVID-19 pandemic are reported. The theoretical and practical implications of the study are also discussed, and, among others, strategic parameters related to machines have been identified and elaborated as enablers of supply chain reconfigurability; the proposed method supports practitioners in improving supply chain resilience and sustainability. The method also encourages practitioners towards the development and adoption of reconfigurable machines. Finally, this study also has social impacts for local communities and stimulates customer-centric collaboration among companies belonging to similar industries and sectors.

Suggested Citation

  • Alessia Napoleone & Alessandro Bruzzone & Ann-Louise Andersen & Thomas Ditlev Brunoe, 2022. "Fostering the Reuse of Manufacturing Resources for Resilient and Sustainable Supply Chains," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:5890-:d:814303
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    References listed on IDEAS

    as
    1. Vladimir Modrak & Zuzana Soltysova, 2021. "Development of the Modularity Measure for Assembly Process Structures," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-9, December.
    2. Alessia Napoleone & Alessandro Pozzetti & Marco Macchi, 2018. "A framework to manage reconfigurability in manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 56(11), pages 3815-3837, June.
    3. M. Reza Abdi & Ashraf Labib, 2017. "RMS capacity utilisation: product family and supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1930-1956, April.
    4. Eduardo Alarcon-Gerbier & Zarina Chokparova & Nassim Ghondaghsaz & Wanqi Zhao & Hani Shahmoradi-Moghadam & Uwe Aßmann & Orçun Oruç, 2022. "Software-Defined Mobile Supply Chains: Rebalancing Resilience and Efficiency in Production Systems," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    5. Armin Jabbarzadeh & Behnam Fahimnia & Fatemeh Sabouhi, 2018. "Resilient and sustainable supply chain design: sustainability analysis under disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5945-5968, September.
    6. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
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