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A Multicomponent Distributed Framework for Smart Production System Modeling and Simulation

Author

Listed:
  • Simon Gorecki

    (University of Bordeaux—IMS UMR CNRS 5218, 33405 Talence CEDEX, France)

  • Jalal Possik

    (Lebanese American University, Department of Computer Science and Mathematics, Block A, Byblos 1401 2010, Lebanon)

  • Gregory Zacharewicz

    (IMT Mines Ales—Laboratoire des Sciences des Risques (LSR), 30319 Alès CEDEX, France)

  • Yves Ducq

    (University of Bordeaux—IMS UMR CNRS 5218, 33405 Talence CEDEX, France)

  • Nicolas Perry

    (Arts et Métiers, University of Bordeaux—I2M UMR CNRS 5295, 33405 Talence CEDEX, France)

Abstract

In order to control manufacturing systems, managers need risk and performance evaluation methods and simulation tools. However, these simulation techniques must evolve towards being multiperformance, multiactor, and multisimulation tools, and this requires interoperability between those distributed components. This paper presents an integrated platform that brings interoperability to several simulation components. This work expands the process modeling tool Papyrus to allow it to communicate with external components through both distributed simulation and cosimulation standards. The distributed modeling and simulation framework (DMSF) platform takes its environment into consideration in order to evaluate the sustainability of the system while integrating external heterogeneous components. For instance, a DMSF connection with external IoT devices has been implemented. Moreover, the orchestration of different smart manufacturing components and services is achieved through configurable business models. As a result, an automotive industry case study has successfully been tested to demonstrate the sustainability of smart supply chains and manufacturing factories, allowing better connectivity with their real environments.

Suggested Citation

  • Simon Gorecki & Jalal Possik & Gregory Zacharewicz & Yves Ducq & Nicolas Perry, 2020. "A Multicomponent Distributed Framework for Smart Production System Modeling and Simulation," Sustainability, MDPI, vol. 12(17), pages 1-26, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6969-:d:404717
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    References listed on IDEAS

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    4. Taylor, Simon J.E., 2019. "Distributed simulation: state-of-the-art and potential for operational research," European Journal of Operational Research, Elsevier, vol. 273(1), pages 1-19.
    5. Zuritah A. Kadir & Roslina Mohammad & Norazli Othman & Astuty Amrin & Mohd Nabil Muhtazaruddin & Siti Hawa Abu-Bakar & Firdaus Muhammad-Sukki, 2020. "Risk Management Framework for Handling and Storage of Cargo at Major Ports in Malaysia towards Port Sustainability," Sustainability, MDPI, vol. 12(2), pages 1-20, January.
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    Cited by:

    1. Govindan, Kannan & Kannan, Devika & Jørgensen, Thomas Ballegård & Nielsen, Tim Straarup, 2022. "Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Athar Ajaz Khan & János Abonyi, 2022. "Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy," Sustainability, MDPI, vol. 14(15), pages 1-40, August.

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