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Evaluating and Ranking the Supplier Selection Criteria for Additive Manufacturing Firms Using Best-Worst Method

In: Advances in Best-Worst Method

Author

Listed:
  • Priya Ambilkar

    (National Institute of Industrial Engineering)

  • Priyanka Verma

    (National Institute of Industrial Engineering)

  • Debabrata Das

    (National Institute of Industrial Engineering)

Abstract

Additive manufacturing (AM) is a well-known technology applied in different industrial applications which have gained more attention over the last three decades. The crucial aspect of AM is designing and managing the supply chain for AM parts. The most critical strategic decision in the initial process of supply chain management is selecting and evaluating suppliers. Selecting an appropriate supplier can lead to reducing costs in supply chain management. Therefore, there is a need to choose a reliable supplier to enhance the performance of their supply network. For the first-time, supplier selection criteria evaluation for the AM domain is examined in this study. This study proposes multi-criteria decision-making based on the best-worst methods to prioritize AM firm’s raw material supplier selection criteria. The best-worst method is generally applied to get the criteria weight. The reliability of the comparisons is checked using a consistency ratio. Then the most important and least important criteria are obtained and considered while selecting a supplier in AM based on the result. Finally, the study concluded the importance of supplier selection for AM. This study further provides a promising avenue for future research opportunities.

Suggested Citation

  • Priya Ambilkar & Priyanka Verma & Debabrata Das, 2023. "Evaluating and Ranking the Supplier Selection Criteria for Additive Manufacturing Firms Using Best-Worst Method," Lecture Notes in Operations Research, in: Jafar Rezaei & Matteo Brunelli & Majid Mohammadi (ed.), Advances in Best-Worst Method, pages 161-175, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-24816-0_13
    DOI: 10.1007/978-3-031-24816-0_13
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