Model‐Driven Engineering for Digital Twins: Opportunities and Challenges

Michael, Judith; Cleophas, Loek; Zschaler, Steffen; Clark, Tony; Combemale, Benoit; Godfrey, Thomas; Khelladi, Djamel Eddine; Kulkarni, Vinay; Lehner, Daniel; Rumpe, Bernhard; Wimmer, Manuel; Wortmann, Andreas; Ali, Shaukat; Barn, Balbir; Barosan, Ion; Bencomo, Nelly; Bordeleau, Francis; Grossmann, Georg; Karsai, Gabor; Kopp, Oliver; Mitschang, Bernhard; Muñoz Ariza, Paula; Pierantonio, Alfonso; Polack, Fiona A. C.; Riebisch, Matthias; Schlingloff, Holger; Stumptner, Markus; Vallecillo, Antonio; van den Brand, Mark; Vangheluwe, Hans

Abstract

Digital twins are increasingly used across a wide range of industries. Modeling is a key to digital twin development—both when considering the models which a digital twin maintains of its real‐world complement (“models in digital twin”) and when considering models of the digital twin as a complex (software) system itself. Thus, systematic development and maintenance of these models is a key factor in effective and efficient digital twin development, maintenance, and use. We argue that model‐driven engineering (MDE), a field with almost three decades of research, will be essential for improving the efficiency and reliability of future digital twin development. To do so, we present an overview of the digital twin life cycle, identifying the different types of models that should be used and re‐used at different life cycle stages (including systems engineering models of the actual system, domain‐specific simulation models, models of data processing pipelines, etc.). We highlight some approaches in MDE that can help create and manage these models and present a roadmap for research towards MDE of digital twins.

Citation

Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., Khelladi, D. E., Kulkarni, V., Lehner, D., Rumpe, B., Wimmer, M., Wortmann, A., Ali, S., Barn, B., Barosan, I., Bencomo, N., Bordeleau, F., Grossmann, G., Karsai, G., Kopp, O., …Vangheluwe, H. (online). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering, https://doi.org/10.1002/sys.21815

• Journal Article Type: Article
• Acceptance Date: Mar 20, 2025
• Online Publication Date: Apr 2, 2025
• Deposit Date: Apr 7, 2025
• Publicly Available Date: Apr 8, 2025
• Journal: Systems Engineering
• Print ISSN: 1098-1241
• Electronic ISSN: 1520-6858
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1002/sys.21815
• Keywords: model‐driven engineering, digital twin, systems engineering, cyber‐physical systems
• Public URL: https://durham-repository.worktribe.com/output/3780723