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CREATION OF DIGITAL TWINS - KEY CHARACTERISTICS OF PHYSICAL TO VIRTUAL TWINNING IN MECHATRONIC PRODUCT DEVELOPMENT

Published online by Cambridge University Press:  27 July 2021

Carolin Sturm*
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Michael Steck
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Frank Bremer
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Sven Revfi
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Thomas Nelius
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Thomas Gwosch
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Albert Albers
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
Sven Matthiesen
Affiliation:
IPEK Institute of Product Engineering, Karlsruhe Institute of Technology (KIT)
*
Sturm, Carolin, Karlsruhe Institute of Technology (KIT), IPEK Institute of Product Engineering, Germany, [email protected]

Abstract

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Due to the falling costs of computational resources and the increasing potential of data acquisition, interest in digital twins, a virtual copy of the physical original, and their industrial application is increasing. Nevertheless, there is limited published work on how to support the process of physical to virtual twinning and what its key aspects are. The aim of this study is to present insights with regards to physical to virtual twinning gained from modelling projects in mechatronic product development. We conducted a survey and in-depth interviews with members of modelling projects. In the surveys and interviews we identified how physical products and virtual models were linked, which virtual models were used and which general challenges and key aspects are considered important by the project members. Our findings show that the key characteristics that pose challenges to modelling regarding physical to virtual twinning are model granularity, model validation, and model integration and interconnectivity.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

Andreasen, M., Hansen, C. and Cash, P. (2015), Conceptual Design, Springer, Cham Heidelberg New York Dordrecht London.CrossRefGoogle Scholar
Boschert, S. and Rosen, R. (2016), “Digital Twin—The Simulation Aspect”, in Hehenberger, P. and Bradley, D. (Eds.), Mechatronic Futures, Springer International Publishing, Cham, pp. 5974.Google Scholar
Glaessgen, E. and Stargel, D., “The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles”, in 53rd AIAA/ASME/ASCE/AHS/ASC Structures.Google Scholar
Grauberger, P., Bremer, F., Sturm, C., Hoelz, K., Wessels, H., Gwosch, T., Wagner, R., Lanza, G., Albers, A. and Matthiesen, S. (2020), “QUALITATIVE MODELLING IN EMBODIMENT DESIGN - INVESTIGATING THE CONTACT AND CHANNEL APPROACH THROUGH ANALYSIS OF PROJECTS”, Proceedings of the Design Society: DESIGN Conference, Vol. 1, pp. 897906.CrossRefGoogle Scholar
Grieves, M. and Vickers, J. (2017), “Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems”, in Kahlen, F.-J., Flumerfelt, S. and Alves, A. (Eds.), Transdisciplinary Perspectives on Complex Systems, Vol. 89, Springer International Publishing, Cham, pp. 85113.CrossRefGoogle Scholar
Haefner, B. and Lanza, G. (2017), “Function-oriented measurements and uncertainty evaluation of micro-gears for lifetime prognosis”, CIRP Annals, Vol. 66 No. 1, pp. 475478.CrossRefGoogle Scholar
Jones, D., Snider, C., Nassehi, A., Yon, J. and Hicks, B. (2020a), “Characterising the Digital Twin: A systematic literature review”, CIRP Journal of Manufacturing Science and Technology, Vol. 29, pp. 3652.CrossRefGoogle Scholar
Jones, D.E., Snider, C. and Hicks, B. (2020b), “A FRAMING OF DESIGN AS PATHWAYS BETWEEN PHYSICAL, VIRTUAL AND COGNITIVE MODELS”, Proceedings of the Design Society: DESIGN Conference, Vol. 1, pp. 4150.CrossRefGoogle Scholar
Maier, J.F., Eckert, C.M. and John Clarkson, P. (2017), “Model granularity in engineering design – concepts and framework”, Design Science, Vol. 3, p. 1.CrossRefGoogle Scholar
Matthiesen, S., Grauberger, P., Bremer, F. and Nowoseltschenko, K. (2019), “Product models in embodiment design: an investigation of challenges and opportunities”, SN Applied Sciences, Vol. 1 No. 9, p. 423.CrossRefGoogle Scholar
Matthiesen, S., Grauberger, P., Sturm, C. and Steck, M. (2018), “From Reality to Simulation – Using the C&C2-Approach to Support the Modelling of a Dynamic System”, Procedia CIRP, pp. 475480.CrossRefGoogle Scholar
Shafto, Mike, Conroy, Mike, Doyle, Rich, Glaessgen, Ed, Kemp, Chris, LeMoigne, Jacqueline and Wang, Lui (2010), “DRAFT Modeling, Simulation, information Technology & Processing Roadmap”, NASA Modeling, Simulation, Information Technology & Processing - TA11.Google Scholar
Riedelsheimer, T., Lünnemann, P., Wehking, S. and Dorfhuber, L. (2020), DIGITAL TWIN READINESS ASSESSMENT: Eine Studie zum Digitalen Zwilling in der Fertigenden Industrie.Google Scholar
Rosen, R., Wichert, G. von, Lo, G. and Bettenhausen, K.D. (2015), “About The Importance of Autonomy and Digital Twins for the Future of Manufacturing”, IFAC-PapersOnLine, Vol. 48 No. 3, pp. 567572.CrossRefGoogle Scholar
Schleich, B., Anwer, N., Mathieu, L. and Wartzack, S. (2017), “Shaping the digital twin for design and production engineering”, CIRP Annals, Vol. 66 No. 1, pp. 141144.CrossRefGoogle Scholar
Schleich, B., Wärmefjord, K., Söderberg, R. and Wartzack, S. (2018), “Geometrical Variations Management 4.0: towards next Generation Geometry Assurance”, Procedia CIRP, Vol. 75, pp. 310.CrossRefGoogle Scholar
Söderberg, R., Wärmefjord, K., Carlson, J.S. and Lindkvist, L. (2017), “Toward a Digital Twin for real-time geometry assurance in individualized production”, CIRP Annals, Vol. 66 No. 1, pp. 137140.CrossRefGoogle Scholar
Söderberg, R., Wärmefjord, K., Madrid, J., Lorin, S., Forslund, A. and Lindkvist, L. (2018), “An information and simulation framework for increased quality in welded components”, CIRP Annals, Vol. 67 No. 1, pp. 165168.CrossRefGoogle Scholar
Stark, R., Anderl, R., Thoben, K.-D. and Wartzack, S. (2020), “WiGeP-Positionspapier: „Digitaler Zwilling“”, ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 115 No. special, pp. 4750.CrossRefGoogle Scholar
Strietzel, M. and Wagner, L. (2020), “Herausforderung Digital Twin: Die digitale Durchgängigkeit erfolgreich gestalten”, NAFEMS DACH Proceedings 2020.Google Scholar
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H. and Sui, F. (2018), “Digital twin-driven product design, manufacturing and service with big data”, The International Journal of Advanced Manufacturing Technology, Vol. 94 No. 9-12, pp. 35633576.CrossRefGoogle Scholar
Wagner, R., Schleich, B., Haefner, B., Kuhnle, A., Wartzack, S. and Lanza, G. (2019), “Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products”, Procedia CIRP, Vol. 84, pp. 8893.CrossRefGoogle Scholar