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Assessing the operational and economic efficiency benefits of dynamic manufacturing networks through fuzzy cognitive maps: a case study

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  • Ourania Markaki

    (National Technical University of Athens)

  • Dimitris Askounis

    (National Technical University of Athens)

Abstract

The formation and effective end-to-end management of manufacturing networks is touted as a top priority for manufacturing enterprises that strive to improve the efficiency, adaptability and sustainability of their production systems. Due to their potential benefits, Dynamic Manufacturing Networks (DMNs), a knowledge-enhanced, model-based production management approach enabling seamless communication and cooperation among individual network members’ manufacturing systems, are gradually becoming a focal point of attention. Nevertheless, current understanding around the DMN concept remains fuzzy, whereas the way in which it can benefit manufacturing enterprises lacks proper articulation. This paper clarifies the management approach of Dynamic Manufacturing Networks on the basis of the DMN lifecycle and the respective information model used, while it further develops a model for their evaluation. In this respect, it employs the soft computing methodology of Fuzzy Cognitive Maps to capture industry laypeople perceptions on the factors that affect their operation, and to reveal insights on prospective benefits. Application of this model in a real-world, multi-site, single factory context in the semi-conductor industry provides good approximations of the experts’ estimations. The results, found in the directions of reduced cycle times, decreased costs and improved quality are quite promising and highlight the key role of the DMN information model. The assessment model designed enables to reason on and identify DMN gains. Thereby, it provides a basis for communication as well as a decision aid that offers evidence on the outcomes of establishing DMNs, ultimately creating a sense of confidence, before an enterprise commits its resources to it.

Suggested Citation

  • Ourania Markaki & Dimitris Askounis, 2021. "Assessing the operational and economic efficiency benefits of dynamic manufacturing networks through fuzzy cognitive maps: a case study," Operational Research, Springer, vol. 21(2), pages 925-950, June.
  • Handle: RePEc:spr:operea:v:21:y:2021:i:2:d:10.1007_s12351-019-00488-y
    DOI: 10.1007/s12351-019-00488-y
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    References listed on IDEAS

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    1. Ricardo Jardim-Goncalves & Antonio Grilo & Keith Popplewell, 2016. "Novel strategies for global manufacturing systems interoperability," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 1-9, February.
    2. F. Tao & Y. Cheng & L. Zhang & A. Y. C. Nee, 2017. "Advanced manufacturing systems: socialization characteristics and trends," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1079-1094, June.
    3. Hammer, Michael & Champy, James, 1993. "Reengineering the corporation: A manifesto for business revolution," Business Horizons, Elsevier, vol. 36(5), pages 90-91.
    4. Seifert, Ralf W. & Langenberg, Kerstin U., 2011. "Managing business dynamics with adaptive supply chain portfolios," European Journal of Operational Research, Elsevier, vol. 215(3), pages 551-562, December.
    5. Alexandros Nikas & Haris Doukas, 2016. "Developing Robust Climate Policies: A Fuzzy Cognitive Map Approach," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 239-263, Springer.
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    1. Themistoklis Koutsellis & Georgios Xexakis & Konstantinos Koasidis & Alexandros Nikas & Haris Doukas, 2022. "Parameter analysis for sigmoid and hyperbolic transfer functions of fuzzy cognitive maps," Operational Research, Springer, vol. 22(5), pages 5733-5763, November.

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