Creating a road map for industry 4.0 by using an integrated fuzzy multicriteria decision-making methodology


Kaya İ. , Erdoğan M., Karaşan A. , Özkan B.

SOFT COMPUTING, cilt.24, ss.17931-17956, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s00500-020-05041-0
  • Dergi Adı: SOFT COMPUTING
  • Sayfa Sayıları: ss.17931-17956

Özet

Industry 4.0 can be defined as a creative manufacturing concept which is the integration of up-to-date technologies such as wireless systems, cyberphysical systems, Internet of things, cloud computing, big data concept to increase flexibility, and speed in production systems. The concept also aims to transform the manufacturing industry into the next generation. Selection among appropriate strategies for transition to industry 4.0 is crucial and should be considered in a multidimensional perspective since the decision process involves many strategies with respect to multicriteria based on the judgments of multiexperts. In this paper, this critical decision has been considered as a multicriteria decision-making (MCDM) problem under the uncertainty and vagueness environments. To increase the applicability of the uncertain data for the proposed methodology, intuitionistic fuzzy sets have been adopted. In other words, an integrated fuzzy MCDM methodology consists of interval-valued intuitionistic fuzzy analytic hierarchy process and interval-valued intuitionistic fuzzy technique for order performance by similarity to ideal solution has been suggested to prioritize of transition strategies for industry 4.0. According to proposed approach, "Training and continuing professional development" is determined as the most important strategy during the transition process, while "Technology" and "Equipment and Tools" are specified as the most crucial main and sub-criterion, respectively. For the validation process, we also applied two distance-based methods on the same decision matrices as a comparative analysis. Both analyses' results yield that the proposed methodology is applicable and effective for the decision-making process. Besides, the results of the one-at-a-time sensitivity analyses based on the changes of main criteria weights confirm the sensitivity and flexibility of the proposed methodology. Finally, a road map for transition to industry 4.0 has been determined with respect to priorities of strategies based on the constructed context.