Skip to main content

Research Repository

Advanced Search

Declarative Lifecycle Management in Digital Twins

Bencomo, Nelly; Kamburjan, Eduard; Tapia Tarifa, Silvia Lizeth; Broch-Johnsen, Einar

  Declarative Lifecycle Management in Digital Twins Thumbnail


Authors

Eduard Kamburjan

Silvia Lizeth Tapia Tarifa

Einar Broch-Johnsen



Abstract

Together, a digital twin and its physical counterpart can be seen as a self-adaptive system: the digital twin monitors the physical system, updates its own internal model of the physical system, and adjusts the physical system by means of controllers in order to maintain given requirements. As the physical system shifts between different stages in its lifecycle, these requirements, as well as the associated analyzers and controllers, may need to change. The exact triggers for such shifts in a physical system are often hard to predict, as they may be difficult to describe or even unknown; however, they can generally be observed once they have occurred, in terms of changes in the system behavior. This paper proposes an automated method for self-adaptation in digital twins to address shifts between lifecycle stages in a physical system. Our method is based on declarative descriptions of lifecycle stages for different physical assets and their associated digital twin components. Declarative lifecycle management provides a high-level, flexible method for self-adaptation of the digital twin to reflect disruptive shifts between stages in a physical system.

Citation

Bencomo, N., Kamburjan, E., Tapia Tarifa, S. L., & Broch-Johnsen, E. (2024, September). Declarative Lifecycle Management in Digital Twins. Presented at 1st International Conference on Engineering Digital Twins (EDTconf 2024), Linz, Austria

Presentation Conference Type Conference Paper (published)
Conference Name 1st International Conference on Engineering Digital Twins (EDTconf 2024)
Start Date Sep 22, 2024
End Date Sep 27, 2024
Acceptance Date Aug 8, 2024
Online Publication Date Oct 31, 2024
Publication Date Oct 31, 2024
Deposit Date Aug 20, 2024
Publicly Available Date Nov 13, 2024
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1145/3652620.3688248
Public URL https://durham-repository.worktribe.com/output/2762606

Files





You might also like



Downloadable Citations