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Contribution to reusability and modularity of manufacturing systems simulation models: Application to distributed control simulation within DFT context

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  • El Haouzi, H.
  • Thomas, A.
  • Pétin, J.F.

Abstract

Requirements for manufacturing control evolve from traditional centralised approaches where decision making is hierarchically broadcasted to more complex distributed control architectures involving autonomous entities and processes. Moreover, manufacturing processes are facing standardisation and globalisation such as promoted by the demand flow technology (DFT) concepts. In order to evaluate these new architectures, discrete-event simulation seems the most appropriate tool. However, complexity of distributed architectures and DFT standardisation requires introducing modularity and reusability in the modelling process. This paper deals with a methodological approach, based on ASDI (analysis-specification-design-implementation), to develop a library of generic simulation components that can be, as automatically as possible, instantiated into a modular simulation model. This approach is illustrated using an industrial case study where simulation aims at evaluating the impact of operator's flexibility induced by DFT context.

Suggested Citation

  • El Haouzi, H. & Thomas, A. & Pétin, J.F., 2008. "Contribution to reusability and modularity of manufacturing systems simulation models: Application to distributed control simulation within DFT context," International Journal of Production Economics, Elsevier, vol. 112(1), pages 48-61, March.
  • Handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:48-61
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    References listed on IDEAS

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    1. Chabrol, Michelle & Sarramia, David & Tchernev, Nikolay, 2006. "Urban traffic systems modelling methodology," International Journal of Production Economics, Elsevier, vol. 99(1-2), pages 156-176, February.
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    Cited by:

    1. Tsegay Tesfay Mezgebe & Hind Bril El Haouzi & Guillaume Demesure & Remi Pannequin & Andre Thomas, 2020. "Multi-agent systems negotiation to deal with dynamic scheduling in disturbed industrial context," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1367-1382, August.

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