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Pipeline for ontology-based modeling and automated deployment of digital twins for planning and control of manufacturing systems

Author

Listed:
  • Amon Göppert

    (RWTH Aachen University)

  • Lea Grahn

    (RWTH Aachen University)

  • Jonas Rachner

    (RWTH Aachen University)

  • Dennis Grunert

    (Fraunhofer Institute for Production Technology IPT)

  • Simon Hort

    (Fraunhofer Institute for Production Technology IPT)

  • Robert H. Schmitt

    (RWTH Aachen University
    Fraunhofer Institute for Production Technology IPT)

Abstract

The demand for individualized products drives modern manufacturing systems towards greater adaptability and flexibility. This increases the focus on data-driven digital twins enabling swift adaptations. Within the framework of cyber-physical systems, the digital twin is a digital model that is fully connected to the physical and digital assets. A digital model must follow a standardization for interoperable data exchange. Established ontologies and meta-models offer a basis in the definition of a schema, which is the first phase of creating a digital twin. The next phase is the standardized and structured modeling with static use-case specific data. The final phase is the deployment of digital twins into operation with a full connection of the digital model with the remaining cyber-physical system. In this deployment phase communication standards and protocols provide a standardized data exchange. A survey on the state-of-the-art of these three digital twin phases reveals the lack of a consistent workflow from ontology-driven definition to standardized modeling. Therefore, one goal of this paper is the design of an end-to-end digital twin pipeline to lower the threshold of creating and deploying digital twins. As the task of establishing a communication connection is highly repetitive, an automation concept by providing structured protocol data is the second goal. The planning and control of a line-less assembly system with manual stations and a mobile robot as resources and an industrial dog as the product serve as exemplary digital twin applications. Along this use-case the digital twin pipeline is transparently explained.

Suggested Citation

  • Amon Göppert & Lea Grahn & Jonas Rachner & Dennis Grunert & Simon Hort & Robert H. Schmitt, 2023. "Pipeline for ontology-based modeling and automated deployment of digital twins for planning and control of manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2133-2152, June.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:5:d:10.1007_s10845-021-01860-6
    DOI: 10.1007/s10845-021-01860-6
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    References listed on IDEAS

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    1. Sebastian R. Bader & Maria Maleshkova & Steffen Lohmann, 2019. "Structuring Reference Architectures for the Industrial Internet of Things," Future Internet, MDPI, vol. 11(7), pages 1-23, July.
    2. Amir Qamar & Mark A. Hall & Simon Collinson, 2018. "Lean versus agile production: flexibility trade-offs within the automotive supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 56(11), pages 3974-3993, June.
    3. Eeva Järvenpää & Niko Siltala & Otto Hylli & Minna Lanz, 2019. "The development of an ontology for describing the capabilities of manufacturing resources," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 959-978, February.
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