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Formal modeling of cyber-physical resource scheduling in IIoT cloud environments

Author

Listed:
  • Shashi Bhushan Jha

    (Embry-Riddle Aeronautical University)

  • Radu F. Babiceanu

    (Embry-Riddle Aeronautical University)

  • Remzi Seker

    (Embry-Riddle Aeronautical University)

Abstract

In the recent years, the topic of Industrial Internet of Things (IIoT) has attracted a large number of academic researchers and industry practitioners. IIoT connects the actors, and the physical and cyber resources of industrial systems, manufacturing- or service-based, in a cloud-enabled overall data exchange system. This work outlines a formal model for operational scheduling of cyber-physical resources for different scenarios determined by resource and logistics availability and cost. Information exchange of physical work-in-process, resource failures, alternative resource options, order and logistics information, are used to deliver real-time scheduling to IIoT participants. The model is formalized using discrete state-machine diagrams for resource reliability and availability status, and logistics timing purposes. Low-performance solution invariants are generated and validated through functional requirements test case building. The data exchange network between the processing nodes of the IIoT environment is built on a software-defined network foundation. A simulation is then built for a series of work-in-process orders and their required processing operations, several manufacturing enterprises and associated physical logistics, and the cloud IIoT network cyber infrastructure for data and control information sharing. Both the formalized and the simulation models are run in the IIoT cloud and can be accessed by the participating enterprises. The formalized model provides insights on resource repair or replacement options, part transfer decisions, while the simulation model builds on those decisions and runs only validated scenarios anchored in timing- and cost-based constraints.

Suggested Citation

  • Shashi Bhushan Jha & Radu F. Babiceanu & Remzi Seker, 2020. "Formal modeling of cyber-physical resource scheduling in IIoT cloud environments," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1149-1164, June.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:5:d:10.1007_s10845-019-01503-x
    DOI: 10.1007/s10845-019-01503-x
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    References listed on IDEAS

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    1. Gregory W. Vogl & Brian A. Weiss & Moneer Helu, 2019. "A review of diagnostic and prognostic capabilities and best practices for manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 79-95, January.
    2. Jeff Morgan & Garret E. O’Donnell, 2018. "Cyber physical process monitoring systems," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1317-1328, August.
    3. André Thomas & Theodor Borangiu & Damien Trentesaux, 2017. "Holonic and multi-agent technologies for service and computing oriented manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1501-1502, October.
    4. Asma Talhi & Virginie Fortineau & Jean-Charles Huet & Samir Lamouri, 2019. "Ontology for cloud manufacturing based Product Lifecycle Management," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2171-2192, June.
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