Abstract
During the entire lifecycle of system development, various digital twins could be developed to support different systems engineering activities, such as verification and validation. The increasing complexity of digital twins leads to a challenge to manage the consistency, changes and traceability across the entire lifecycle. In this paper, a semantics modeling approach is provided to formalize the digital twins using systems thinking. The semantic models represent the information of each digital twin and the interrelationships among them. Using the semantic models, system developers are enabled to promote the cognitive capabilities of digital twins, which in return will provide more potentials for decision-makings based on digital twins. Finally, the feasibility of the proposed approach is evaluated through a case study in the Swiss Innovation Project IMPURSE.
Jinzhi Lu is a research scientist in ICT4SM group at EPFL.
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Acknowledgements
The work presented in this paper is supported by the EU H2020 project (869951) FACTLOG-Energy-aware Factory Analytics for Process Industries and EU H2020 project (825030) QU4LITY Digital Reality in Zero Defect Manufacturing and the InnoSwiss IMPULSE project on Digital Twins.
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Lu, J., Zheng, X., Schweiger, L., Kiritsis, D. (2021). A Cognitive Approach to Manage the Complexity of Digital Twin Systems. In: West, S., Meierhofer, J., Ganz, C. (eds) Smart Services Summit. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-030-72090-2_10
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