Article Dans Une Revue SIMULATION: Transactions of The Society for Modeling and Simulation International Année : 2024

Formalizing a framework of inference capabilities for Digital Twin engineering

Résumé

Nowadays, smart systems require the use of Digital Twins (DTs) for their engineering and management. Self-updating capability is a key feature in the DT technology. This raises the challenge of model inference from data collected on the system and requires a formal framework be defined, in which a system representation can be coupled with inference methods to achieve automatic model updating. While data-based process model inference is a well-known technique, the inference of a simulation model from existing knowledge and collected data is yet an unexplored area. In this paper, we first clarify and explicitly define some key elements of the terminology related to the DT concept, including model update and model inference, and we propose a framework of inference capabilities based on a formal DT specification, which formally captures the conditions for different updating capabilities and relates them. That way, on one hand, the framework enables the use of symbolic approaches to build a DT with the desired inference capability, and on the other hand, it establishes a partial order relation between inference capabilities. Through a case study, we show how the framework helps formally specifying the DT model of a mobility system toward realizing a fully capable DT.
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Dates et versions

hal-04692929 , version 1 (10-09-2024)

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Citer

Mama Diakité, Mamadou Kaba Traore. Formalizing a framework of inference capabilities for Digital Twin engineering. SIMULATION: Transactions of The Society for Modeling and Simulation International, 2024, 100 (9), ⟨10.1177/00375497241228281⟩. ⟨hal-04692929⟩
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