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Fuzzy holons for intelligent multi-scale design in cloud-based design for configurations

Author

Listed:
  • Homam Issa

    (Université de Technologie de Belfort-Montbéliard)

  • Egon Ostrosi

    (Université de Technologie de Belfort-Montbéliard)

  • Michel Lenczner

    (Université de Technologie de Belfort-Montbéliard)

  • Rabie Habib

    (Tishreen University)

Abstract

Cloud-based design for configurations can be referred to as a service-oriented networked design for configurations model. However, cloud-based models also pose challenges such as reliability, availability, capability, ability, adaptability of resources, and services across spatial boundaries. Multi-scale design can presumably stimulate greater intelligence in cloud-based models. Using the concepts of the fuzzy holon and the fuzzy attractor, this paper proposes the fuzzy holonic approach to address multi-scale design for configurations. A fuzzy design holon is defined through two basic holons: fuzzy function holon and fuzzy solution holon. A fuzzy attractor is defined as a fuzzy function holon or fuzzy function solution toward which a design tends to evolve. The proposed fuzzy holon model is driven by two conflicting drives: (a) completeness of fuzzy function holons and fuzzy solution holons, and (b) discrimination of fuzzy function holons and fuzzy solution holons. Through simulations, four possible states of behavior of fuzzy holon design are found: (a) the impossibility state characterized by the impossibility of fuzzy holon creation; (b) the creation and destruction state sometimes characterized by the creation of fuzzy holons and sometimes the destruction of fuzzy holons, (c) the development state characterized by a natural creation and development of fuzzy holons and (d) the failure state characterized by the interruption of the development of the fuzzy design holon and the destruction of already created fuzzy design holon. The model explains that design is not an orderly and well behaved phenomenon. It shows that fuzzy holon design is a discontinuous phenomenon.

Suggested Citation

  • Homam Issa & Egon Ostrosi & Michel Lenczner & Rabie Habib, 2017. "Fuzzy holons for intelligent multi-scale design in cloud-based design for configurations," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1219-1247, June.
  • Handle: RePEc:spr:joinma:v:28:y:2017:i:5:d:10.1007_s10845-015-1119-4
    DOI: 10.1007/s10845-015-1119-4
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
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    Cited by:

    1. Gui Li & Xiaoyu Long & Min Zhou, 2019. "A new design method based on feature reusing of the non-standard cam structure for automotive panels stamping dies," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2085-2100, June.
    2. Liang Hou & Roger J. Jiao, 2020. "Data-informed inverse design by product usage information: a review, framework and outlook," Journal of Intelligent Manufacturing, Springer, vol. 31(3), pages 529-552, March.

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