Twins Interoperability through Service Oriented Architecture: A use-case of Industry 4.0.
Acharya, Sarthak; Wintercorn, Oskar; Tripathy, Aparajta; Hanif, Muhammad; Van Deventer, Jan; Päivärinta, Tero (2023-06-14)
R. Piskac c/o Redaktion Sun SITE, Informatik V, RWTH Aachen
14.06.2023
Archarya, S., Wintercorn, O., Tripathy, A., Hanif, M., Van Deventer, J. & Päivärinta, T. (2023). Twins Interoperability through Service Oriented Architecture: A use-case of Industry 4.0. In J. Kasurinen & T. Päivärinta (Eds.), Proceedings of the Annual Symposium of Computer Science 2023 co-located with The International Conference on Evaluation and Assessment in Software Engineering (EASE 2023), 3506, pp. 107-115, https://ceur-ws.org/Vol-3506/shortpaper09.pdf
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© 2023 for the individual papers by the papers' authors. Copyright © 2023 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).
https://creativecommons.org/licenses/by/4.0/
© 2023 for the individual papers by the papers' authors. Copyright © 2023 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202401161255
https://urn.fi/URN:NBN:fi:oulu-202401161255
Tiivistelmä
Abstract
Since Industry 4.0 technologies were introduced, manufacturing processes have continued to evolve with, for example, Artificial intelligence (AI), the industrial Internet of things (IIoT), robotics, digital twin technology, and other cutting-edge innovations to empower intelligent manufacturing processes. Nonetheless, there remain obstacles to integration within and optimization of systems of systems. An open-source micro-service architecture can alleviate these hurdles. To demonstrate interoperability between technologies, we have chosen to conduct our research using a physical training factory from Fischertechnik with different digital twins (DTs). In this paper, one digital replica of the physical factory is implemented using a three-dimensional CAD tool (Siemens NX-MCD), while the second is an information-centric digital twin created using Eclipse Ditto. The work is focused on creating digital twins of individual sections of the full factory to achieve interoperability, incorporating open-source frameworks to achieve interoperability and systems binding at run-time, and adapting multiple protocol communications in twins. This work is in progress and foresees two scenarios as its further development. The first is the digital twin’s ability to facilitate predictive maintenance. Secondly, the use of an information-centric digital twin in the loop to constantly monitor the production process in the event of connectivity issues.
Since Industry 4.0 technologies were introduced, manufacturing processes have continued to evolve with, for example, Artificial intelligence (AI), the industrial Internet of things (IIoT), robotics, digital twin technology, and other cutting-edge innovations to empower intelligent manufacturing processes. Nonetheless, there remain obstacles to integration within and optimization of systems of systems. An open-source micro-service architecture can alleviate these hurdles. To demonstrate interoperability between technologies, we have chosen to conduct our research using a physical training factory from Fischertechnik with different digital twins (DTs). In this paper, one digital replica of the physical factory is implemented using a three-dimensional CAD tool (Siemens NX-MCD), while the second is an information-centric digital twin created using Eclipse Ditto. The work is focused on creating digital twins of individual sections of the full factory to achieve interoperability, incorporating open-source frameworks to achieve interoperability and systems binding at run-time, and adapting multiple protocol communications in twins. This work is in progress and foresees two scenarios as its further development. The first is the digital twin’s ability to facilitate predictive maintenance. Secondly, the use of an information-centric digital twin in the loop to constantly monitor the production process in the event of connectivity issues.
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