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SysML 4 Digital Twins – Utilization of System Models for the Design and Operation of Digital Twins

Published online by Cambridge University Press:  26 May 2022

F. Wilking*
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
C. Sauer
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
B. Schleich
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
S. Wartzack
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

Abstract

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The implementation of Digital Twins has become a common task for many industrial companies to ensure a sufficient digitization of their products and maintain competitiveness. This results in the question of how to compensate additional effort caused by designing Digital Twins. With this paper, an approach for this compensation is presented by creating Digital Twin behaviour through utilizing SysML diagrams and directly derivate usable code from them for a further implementation. This offers a part solution of lowering the threshold for using MBSE and increasing its benefits.

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), 2022.

References

Bao, J., Guo, D., Li, J. and Zhang, J. (2019), “The modelling and operations for the digital twin in the context of manufacturing”, Enterprise Information Systems, Vol. 13 No. 4, pp. 534556. https://dx.doi.org/10.1080/17517575.2018.1526324.Google Scholar
Eigner, M., Huwig, C. and Dickopf, T. (2015), “Cost-Benefit Analysis in Model-Based Systems Engineering: State of the Art and Future Potentials”, in– Proceedings of the 20th International Conference on Engineering Design (ICED15), pp. 227236.Google Scholar
Gartner (2018), “Hype Cycle for Emerging Technologies”, https://www.gartner.com/smarterwithgartner/5-trends-emerge-in-gartner-hype-cycle-for-emerging-technologies-2018/ (accessed 21 July 2020).Google Scholar
Handley, H.A.H., Khallouli, W., Huang, J., Edmonson, W. and Kibret, N. (2021), “Maintaining the Consistency of SysML Model Exports to XML Metadata Interchange (XMI)”, in 2021 IEEE International Systems Conference (SysCon), Vancouver, BC, Canada, IEEE, pp. 18. https://dx.doi.org/10.1109/SysCon48628.2021.9447105.Google Scholar
Honour, E.C. (2013), “Systems Engineering Return on Investment”, Dissertation, Defence and Systems Institute, University of South Australia, 2013.Google Scholar
Hribernik, K., Wuest, T. and Thoben, K.-D. (2013), “Towards Product Avatars Representing Middle-of-Life Information for Improving Design, Development and Manufacturing Processes”, in Kovács, G.L. and Kochan, D. (Eds.), IFIP TC 5 International Conference, NEW PROLAMAT 2013, Dresden, Germany20, pp. 8596.Google Scholar
Kapos, G.-D., Dalakas, V., Nikolaidou, M. and Anagnostopoulos, D. (2014), “An integrated framework for automated simulation of SysML models using DEVS”, SIMULATION, Vol. 90 No. 6, pp. 717744. https://dx.doi.org/10.1177/0037549714533842.Google Scholar
Karban, R., Dekens, F.G., Herzig, S., Elaasar, M. and Jankevičius, N. (2016), “Creating system engineering products with executable models in a model-based engineering environment”, in Angeli, G.Z. and Dierickx, P. (Eds.), Modeling, Systems Engineering, and Project Management for Astronomy VI, 2016, Edinburgh, United Kingdom, SPIE, 99110B. https://dx.doi.org/10.1117/12.2232785.Google Scholar
Lee, J., Lapira, E., Bagheri, B. and Kao, H. (2013), “Recent advances and trends in predictive manufacturing systems in big data environment”, Manufacturing Letters, (1). 3841. https://dx.doi.org/10.1016/j.mfglet.2013.09.005.CrossRefGoogle Scholar
Mahboob, A., Husung, S., Weber, C., Liebal, A. and Krömker, H. (2018), “SysML Behaviour Models for Description of Virtual Reality Environments for Early Evaluation of a Product”, in Proceedings of the DESIGN 2018 15th International Design Conference, pp. 29032912. https://dx.doi.org/10.21278/idc.2018.0382.CrossRefGoogle Scholar
Makarov, V.V., Frolov, Y., Parshina, I.S. and Ushakova, M.V. (2019), “The Design Concept of Digital Twin”, in Cvirkun, A.D. (Ed.), Proceedings of 2019 Twelfth International Conference MLSD: Russia, pp. 14. https://dx.doi.org/10.1109/MLSD.2019.8911091.Google Scholar
Rosen, R., von, Wichert, G., 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. https://dx.doi.org/10.1016/j.ifacol.2015.06.141.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. https://dx.doi.org/10.1016/j.cirp.2017.04.040.Google Scholar
Schleich, B., Dittrich, M.-A., Clausmeyer, T., Damgrave, R., Erkoyuncu, J.A., Haefner, B., de, Lange, J., Plakhotnik, D., Scheidel, W. and Wuest, T. (2019), “Shifting value stream patterns along the product lifecycle with digital twins”, Procedia CIRP, Vol. 86, pp. 311. https://dx.doi.org/10.1016/j.procir.2020.01.049.CrossRefGoogle Scholar
Schroeder, G.N., Steinmetz, C., Pereira, C.E. and Espindola, D.B. (2016), “Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange”, IFAC-PapersOnLine, Vol. 49 No. 30, pp. 1217. https://dx.doi.org/10.1016/j.ifacol.2016.11.115.Google Scholar
Schumacher, T. and Inkermann, D. (2021), “Heterogene Modellierung - Verknüpfung und Integration von Systemmodellen der SysML mit CAD-Modellen”, in: Proceedings of the 32nd Symposium Design for X, The Design Society. https://dx.doi.org/10.35199/dfx2021.20.CrossRefGoogle Scholar
Sheard, S., Cook, S., Honour, E., Hybertson, D., Krupa, J., McEver, J., McKinney, D., Ondrus, P.: Ryan, A., Scheurer, R., Singer, J., Sparber, J. and White, B. (2015), A Complexity Primer for Systems Engineers.Google 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. https://dx.doi.org/10.3139/104.112311.CrossRefGoogle Scholar
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Guo, Z., Lu, S.C.-Y. and Nee, A.Y.C. (2019), “Digital twin-driven product design framework”, International Journal of Production Research, Vol. 57 No. 12, pp. 39353953. https://dx.doi.org/10.1080/00207543.2018.1443229.Google Scholar
Wang, Y., Steinbach, T., Klein, J. and Anderl, R. (2021), “Integration of model based system engineering into the digital twin concept”, Procedia CIRP, Vol. 100, pp. 1924. https://dx.doi.org/10.1016/j.procir.2021.05.003.Google Scholar
Weilkiens, T. (2014), Systems Engineering mit SysML/UML: Anforderungen, analyse, architektur, Germany.Google Scholar
Wilking, F., Schleich, B. and Wartzack, S. (2020), “MBSE along the Value Chain – An Approach for the Compensation of additional Effort”, in 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE), Budapest, Hungary, IEEE, pp. 6166. https://dx.doi.org/10.1109/SoSE50414.2020.9130497.CrossRefGoogle Scholar
Wilking, F., Schleich, B. and Wartzack, S. (2021), “DIGITAL TWINS - DEFINITIONS, CLASSES AND BUSINESS SCENARIOS FOR DIFFERENT INDUSTRY SECTORS”, Proceedings of the Design Society, Vol. 1M, pp. 12931302. https://dx.doi.org/10.1017/pds.2021.129.CrossRefGoogle Scholar