Digital Twins

Research and industry leverage digital twins to monitor and control (cyber-physical) systems in various domains, including automotive, avionics, biology, construction, manufacturing, medicine, and many more. They promise a tremendous potential to reduce cost and time and improve our understanding of the represented systems. The various digital twins serve different purposes, including analysis, control, and behavior prediction, and they are used at different times relative to the represented system, e.g., before it exists to explore its design space or during its runtime to optimize its behavior. Despite a plethora of definitions, there is little consensus about what a digital twin is.

This also is reflected in many of the available definitions being

  • ambiguous, by deferring to another undefined term, such as a “virtual representation”, a “computable virtual abstraction” , or a “a virtual projection of the industrial facility into the cloud”
  • narrow, by focusing on specific use cases, domains, or technologies, such as a “digital model of the real network environment” or a “virtual representation based on AR technology”
  • utopian, due to all-encompassing aspirations, such as an “integrated virtual model of a real-world system containing all of its physical information”, a “complete digital representation”.

For us, a digital twin is a software system that leverages models and data from and about an original (cyber-physical) system, to represent, predict, and prescribe its behavior for a specific purpose.

This entails that a digital twin

  • is neither bound to specific technology or application domain
  • does not need to be complete (which is impossible most of the time)
  • does not need to be a model but may use models
  • may change the behavior of the original system

From this, interesting questions arise. Some of which I have discussed in my talk Ceci n’est pas un jumeau numérique in the Engineering Digital Twins Community.

Selected publications below highlight how we leverage this notion of digital twins to facilitate their engineering and operations

10 Selected Publications

  1. Pfeiffer, J., Zhang, J., Combemale, B., Michael, J., Rumpe, B., Wimmer, M., & Wortmann, A. (2025). Towards a Unifying Reference Model for Digital Twins of Cyber-Physical Systems.In ETFA 2025. IEEE. (to appear)
  2. Kimmel, R., Michael, J., Wortmann, A., & Zhang, J. (2025). Digital Twins for Software Engineering Processes. In 2025 IEEE/ACM 47th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) (pp. 16-20). IEEE.
  3. Michael, J., Cleophas, L., Zschaler, S., Clark, T., Combemale, B., Godfrey, T., … & Vangheluwe, H. (2025). Model‐Driven Engineering for Digital Twins: Opportunities and Challenges. Systems Engineering. Wiley.
  4. Lehner, D., Zhang, J., Pfeiffer, J., Sint, S., Splettstößer, A. K., Wimmer, M., & Wortmann, A. (2025). Model-driven engineering for digital twins: a systematic mapping study. Software and Systems Modeling, 1-39.
  5. Zhang, J., Ellwein, C., Heithoff, M., Michael, J., & Wortmann, A. (2025). Digital twin and the asset administration shell: An Analysis of the Three Types of AASs and their Feasibility for Digital Twin Engineering. Software and Systems Modeling, 1-23.
  6. Heithoff, M., Michael, J., Rumpe, B., Pfeiffer, J., Wortmann, A., & Zhang, J. (2025). A Method for Model-Driven Engineering of Digital Twins in Manufacturing. In MODELS 2025. ACM. (to appear)
  7. Eramo, R., Bordeleau, F., Combemale, B., van Den Brand, M., Wimmer, M., & Wortmann, A. (2021). Conceptualizing Digital Twins. IEEE Software, 39(2), 39-46.
  8. Bolender, T., Bürvenich, G., Dalibor, M., Rumpe, B., & Wortmann, A. (2021, May). Self-Adaptive Manufacturing with Digital Twins. In 2021 International symposium on software engineering for adaptive and self-managing systems (SEAMS) (pp. 156-166). IEEE.
  9. Bibow, P., Dalibor, M., Hopmann, C., Mainz, B., Rumpe, B., Schmalzing, D., … & Wortmann, A. (2020). Model-Driven Development of a Digital Twin for Injection Molding. In International Conference on Advanced Information Systems Engineering (pp. 85-100). Cham: Springer International Publishing.
  10. Kirchhof, J. C., Michael, J., Rumpe, B., Varga, S., & Wortmann, A. (2020). Model-Driven Digital Twin Construction. Synthesizing the Integration of Cyber-Physical Systems with Their Information Systems. In Proceedings of the 23rd ACM/IEEE international conference on model driven engineering languages and systems (pp. 90-101).

Find more publications on digital twins.

Find other research topics from my research website.

Digital Twins in Various Domains

We have conducted the largest systematic mapping study on digital twins across domains. In this study, we have, ultimately, investigated a corpus of over 2000 publications to find out how digital twins are engineered, operated, and what the major challenges are.

You can find the domains in which digital twins are used and the related publications below. If there are mistakes in the author names, please inform the publisher of your choice to provide proper publication data export.

Domains

  1. Construction
  2. Education
  3. Energy
  4. Health
  5. ICT
  6. Manufacturing
  7. Transport and Storage

Construction

Education

Energy

Health

ICT

Manufacturing

Mining

Transport and Storage

Find other research topics from my research website.