Towards an adaptive model for collaborative simulation: from system design to lessons learned. A use case from Aircraft industry

Laura Roa Castro (), Julie Stal-Le Cardinal () and Martine Callot
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Laura Roa Castro: IRT SystemX, LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec
Julie Stal-Le Cardinal: LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec
Martine Callot: EADS CCR - EADS Corporate Research Center - Airbus Groups Innovations

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Abstract: Over the last few years, vehicle industry has been looking for a better preparation of test and certification phases of their complex products. In this context, Modelling and Simulation (M&S) technics have grown in importance for these companies. Since M&S technics are growing on, the number of people performing those technics have risen exponentially, making their teams work harder to accomplish the simulation objectives. Different alternatives supporting collaborative simulation have been proposed. Nevertheless, most of those alternatives deal only with Information and Technical (IT) problems. This paper proposes the considered solutions, based on a use case from aircraft industry, aiming at develop an adaptive model for collaborative simulation. The results include a holistic view of collaborative problems in simulation processes, distinguished between three different phases: initialization, collaboration and return of experience. In addition, the model combines also three main parts for a successful collaboration: the actors, the process and the objects to exchange. The adaptive model developed gives a clear idea of dynamic interactions between the different phases. Future work will consider a cooperative model based on game theory in order to establish the actors behavior model

Keywords: Collaborative simulation; actor based approach; simulation model exchange; Concurrent engineering (search for similar items in EconPapers)
Date: 2015-11-02
New Economics Papers: this item is included in nep-cmp
Note: View the original document on HAL open archive server: https://hal.science/hal-01356853v1
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Published in Complex Adaptive Systems Conference, Nov 2015, San Jose, CA, United States. pp.267-273, ⟨10.1016/j.procs.2015.09.212⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01356853

DOI: 10.1016/j.procs.2015.09.212

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