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Declarative Lifecycle Management in Digital Twins

  • ,
  • Nelly Bencomo
    ,
  • Silvia Lizeth Tapia Tarifa
    ,
  • Einar Broch Johnsen
  • University of Oslo
    ,
  • Durham University
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 353-363 (11 pages)

Publication milestones

  • Published - 31/10/2024

Publication status

Published - 31/10/2024

Publisher

Association for Computing Machinery, United States
9798400706226

Publication IDs

  • Scopus: 85212231239

Host publication title

Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems

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.

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Captures
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Citations
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Related Event

Title

International Conference on Model Driven Engineering Languages and Systems

Event type

Conference

Degree of recognition

International event

Date

22/09/2024 - 27/09/2024

Location

LinzAustria