An integrated interval type 2 fuzzy AHP and COPRAS-G methodologies for supplier selection in the era of Industry 4.0

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Kayapinar Kaya S., Ayçın E.

Neural Computing and Applications, 2021 (Journal Indexed in SCI Expanded) identifier

  • Publication Type: Article / Article
  • Volume:
  • Publication Date: 2021
  • Doi Number: 10.1007/s00521-021-05809-x
  • Title of Journal : Neural Computing and Applications


© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.Supply chain has a very extensive and dynamic structure that incorporates new business models, new customer expectations, market searches and technological developments. With the introduction of Industry 4.0 into supply chain, a rapid and intensive process of digitalization begins to transform every step of supply chain. Supply chain selection is one of the essential decisions in reducing the supply chain cost and improving overall quality of product and services. With the implication of digital technologies and Industry 4.0 on supply chain, the supplier selection process has been significantly changed during the recent years. Companies are willing to need new requirements for their own suppliers in accordance with Industry 4.0 implementations and technologies. This paper aims to identify key criteria to Industry 4.0 technologies and evaluate them to select the right suppliers selection in the era of Industry 4.0. Within the scope of this study attempts to develop an integrated interval type 2 fuzzy AHP and GOPRAS-G methodology to select the appropriate supplier in the face of Industry 4.0 implementations. For this purpose, interval type 2 fuzzy AHP was employed to weight the supplier evaluation criteria and then, Gray COPRAS method has been applied to prioritize suppliers. This paper is to provide practitioners and researchers with insight into how Industry 4.0 strategies influence on supplier selection.