4.7 Article

Intelligent sustainable supplier selection using multi-agent technology: Theory and application for Industry 4.0 supply chains

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 127, Issue -, Pages 588-600

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2018.10.050

Keywords

Sustainable supplier selection; Industry 4.0; Multi-agent systems; Cyber-physical systems; Industry 4.0 supply chain

Funding

  1. National Natural Science Foundation of China [61603011, 61773029, 71772016]
  2. Beijing Social Science Foundation [16JDGLC005]
  3. International Postdoctoral Exchange Fellowship Program [20170016]
  4. China Postdoctoral Science Foundation [2015M580033]
  5. Beijing Postdoctoral Science Foundation [2016ZZ-11]
  6. Great Wall Scholar Training Program of Beijing Municipality [CITTCD20180305]
  7. Electronic Component Systems for European Leadership Joint Undertaking from the European Union's Horizon 2020 research and innovation program [737459]
  8. Science Foundation Ireland (SFI) [European Regional Development Fund] [16/RC/3918]

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Advancements in information and communication systems offer immense opportunities for supply chain intelligence and autonomy establishing stepping stones for Industry 4.0 supply chains (SCs). As a crucial SC decision, sustainable supplier evaluation and selection process have been addressed abundantly in the previous literature. However, this process has not yet been realized within Industry 4.0 SCs where interconnection, real-time information transparency, technical assistance and decentralization of members of a physical system (i.e., supply chain members) are regarded as the main design principles. To narrow the identified gap, a Multi-Agent Systems (MASs) approach is proposed for addressing sustainable supplier evaluation and selection process to provide a proper communication channel, structured information exchange and visibility among suppliers and manufacturers. Furthermore, the application of MASs in this process and their natural applicability as one of the enabling technologies in moving towards Industry 4.0 SCs are investigated in detail. It is found that the proposed approach can help decision-makers inside manufacturing firms to make prompt decisions with less human interactions. The merit of the developed MAS is demonstrated through a real-world implementation on a medical device manufacturer. Finally, the limitations and advantages of the proposed approach are presented together with some remarks for future work.

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