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A survey on the industry's perception of digital twins – a follow-up to the digital twin workshop at the DESIGN Conference 2022

Published online by Cambridge University Press:  16 May 2024

Michel Fett ,
Julius Zwickler ,
Fabian Wilking ,
Stefan Goetz ,
Sebastian Schweigert-Recksiek ,
Ben Hicks ,
Oscar Nespoli ,
Kristina Wärmefjord ,
Sandro Wartzack  and
Eckhard Kirchner
Michel Fett*
Affiliation:
Technische Universität Darmstadt, Germany
Julius Zwickler
Affiliation:
Technische Universität Darmstadt, Germany
Fabian Wilking
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Stefan Goetz
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Sebastian Schweigert-Recksiek
Affiliation:
:em engineering methods AG, Germany
Ben Hicks
Affiliation:
University of Bristol, United Kingdom
Oscar Nespoli
Affiliation:
University of Waterloo, Canada
Kristina Wärmefjord
Affiliation:
Chalmers University of Technology, Sweden
Sandro Wartzack
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Eckhard Kirchner
Affiliation:
Technische Universität Darmstadt, Germany
*
michel.fett@tu-darmstadt.de

Abstract

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Digital Twins are perceived differently between and within industry and academia regarding applications and potentials. For this reason, a round table was formed based on the Digital Twin Workshop of the Design Conference 2022. One of the results of this round table is this contribution, which deals with a survey within the industry. The survey captured the understanding of the different roles in the creation and use of Digital Twins, the requirements and hurdles as well as the perception of methodological support. In addition, factors that influence the perception were identified.

Keywords

digital twinsurveydesign workshopindustry 4.0
Type
Artificial Intelligence and Data-Driven Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2039 - 2048
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), 2024.

References

Ali, M.E., Cheema, M.A., Hashem, T., Ulhaq, A. and Babar, M.A. (2023), "Enabling Spatial Digital Twins: Technologies, Challenges, and Future Research Directions."CrossRefGoogle Scholar
Biesinger, F., Kras, B. and Weyrich, M. (2019), “A Survey on the Necessity for a Digital Twin of Production in the Automotive Industry”, Proceeding of International Conference on Mechatronics Technology (ICMT), IEEE, Salerno, Italy, pp. 1–8. https://doi.org/10.1109/ICMECT.2019.8932144Google Scholar
Chernoff, H. and Lehmann, E.L. (1954), “The Use of Maximum Likelihood Estimates in Chi2 Tests for Goodness of Fit”, The Annals of Mathematical Statistics, Vol. 25 No. 3, pp. 579–586. https://doi.org/10.1007/978-1-4614-1412-4_47CrossRefGoogle Scholar
Czwick, C., Martin, G., Anderl, R. and Kirchner, E. (2020), “Cyber-Physische Zwillinge”, Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 115 No. 1, pp. 90–93. https://doi.org/10.3139/104.112310CrossRefGoogle Scholar
Fett, M., Wilking, F., Goetz, S., Kirchner, E. and Wartzack, S. (2023a), "Sensor selection and integration for Cyber-Physical Systems in context of Digital Twins – A systematic review of requirements," 2023 18th Annual System of Systems Engineering Conference (SoSe), pp. 1-7, https://dx.doi.org/10.1109/SoSE59841.2023.10178669.CrossRefGoogle Scholar
Diego, Hoz, de, J.D., Temperekidis, A., Katsaros, P. and Konstantinou, C. (2022), “An IoT Digital Twin for Cyber-Security Defence Based on Runtime Verification”, International Symposium on Leveraging Applications of Formal Methods, Springer, Cham, pp. 556–574. https://doi.org/10.1007/978-3-031-19849-6_31CrossRefGoogle Scholar
Lei, B., Janssen, P., Stoter, J. and Biljecki, F. (2023), “Challenges of urban digital twins: A systematic review and a Delphi expert survey”, Automation in Construction, Vol. 147, p. 104716. https://doi.org/10.1016/j.autcon.2022.104716CrossRefGoogle Scholar
Li, J., Zhou, G. and Zhang, C. (2022), “A twin data and knowledge-driven intelligent process planning framework of aviation parts”, International Journal of Production Research, Vol. 60 No. 17, pp. 5217–5234. https://doi.org/10.1080/00207543.2021.1951869CrossRefGoogle Scholar
Plackett, R.L. (1983), “Karl Pearson and the Chi-Squared Test”, International Statistical Review / Revue Internationale de Statistique, Vol. 51 No. 1, p. 59-72. https://doi.org/10.2307/1402731Google Scholar
Stark, R., Anderl, R., Thoben, K.-D. and Wartzack, S. (2020), “WiGeP-Positionspapier: „Digitaler Zwilling“”, Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol. 115 No. s1, pp. 47–50. https://doi.org/10.3139/104.112311CrossRefGoogle Scholar
Trauer, J., Schweigert-Recksiek, S., Engel, C., Spreitzer, K. and Zimmermann, M. (2020), "What Is a Digital Twin? – Definitions and Insights from an Industrial Case Study in Technical Product Development," Proceedings of the Design Society: DESIGN Conference, Vol. 1, pp. 757–766. https://doi.org/10.1017/dsd.2020.15Google Scholar
Udugama, I., Öner, M., Lopez, P.C., Beenfeldt, C., Bayer, C., Huusom, J.K., Gernaey, K.V. and Sin, G. (2021), “Towards Digitalization in Bio-Manufacturing Operations: A Survey on Application of Big Data and Digital Twin Concepts in Denmark”, Frontiers in Chemical Engineering, Vol. 3. https://doi.org/10.3389/fceng.2021.727152CrossRefGoogle Scholar
Wang, B., Zhou, H., Yang, G., Li, X. and Yang, H. (2022), “Human Digital Twin (HDT) Driven Human-Cyber-Physical Systems: Key Technologies and Applications”, Chinese Journal of Mechanical Engineering, Vol. 35 No. 1. https://doi.org/10.1186/s10033-022-00680-wCrossRefGoogle 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. 1, pp. 1293–1302. https://doi.org/10.1017/pds.2021.129CrossRefGoogle Scholar
Yates, F. (1934), “Contingency Tables Involving Small Numbers and the χ 2 Test”, Supplement to the Journal of the Royal Statistical Society, Vol. 1 No. 2, p. 217. https://doi.org/10.2307/2983604Google Scholar