Abstract
The availability of machine-generated data for the management of complex systems enables run-time technologies for diagnosis, predictive maintenance, process control, etc. that find their apex in digital twins. Such model-based replica of cyber-physical assets represent system elements and their behavior within their environment, which is often dynamic. These dynamics of a system’s environment can render the underlying model unfit w.r.t. the changing reality and thus cripple the whole approach. We provide the means to detect such a transgression of the operational space of digital twins and similar technologies using a novel combination of probability-of-findings calculations with established process control methods and localize necessary updates to ensure efficient model maintenance.
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Borth, M., van Gerwen, E. (2019). Tracking Dynamics in Concurrent Digital Twins. In: Bonjour, E., Krob, D., Palladino, L., Stephan, F. (eds) Complex Systems Design & Management. CSD&M 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-04209-7_6
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DOI: https://doi.org/10.1007/978-3-030-04209-7_6
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