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

Alessia Napoleone, Alessandro Bruzzone, Ann-Louise Andersen, Thomas Ditlev Brunø

Research output: Contribution to journalJournal articleResearchpeer-review

10 Citations (Scopus)
73 Downloads (Pure)

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.
Original languageEnglish
Article number5890
JournalSustainability
Volume14
Issue number10
ISSN2071-1050
DOIs
Publication statusPublished - May 2022

Keywords

  • mixed integer programming
  • reconfigurable manufacturing
  • resilience
  • reuse
  • supply chain
  • sustainability

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