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.
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The research leading to these results has been supported by the EC 7th Framework Programme under the project “IMAGINE—Innovative end-to-end management of Dynamic Manufacturing Networks” Grant Agreement Νο. 285132.
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