Adaptation framework for an industrial digital twin
Koistinen, Antti; Ohenoja, Markku; Tomperi, Jani; Ruusunen, Mika (2020-12-31)
Pulkkinen, Jari; Louis, Jean-Nicolas (2020) Impacts of demand side management programs to domestic hot water heating load profiles in smart buildings. In : In E. Juuso, B. Lie, E. Dahlquist & J. Ruuska (Eds.), Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, Virtual Conference, Finland, 22-24 September 2020. Linköping electronic conference proceedings, 176, 1-8. https://doi.org/10.3384/ecp20176365
© 2020 The authors. Creative Commons Attribution 4.0 (CC-BY) licence. https://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2021120158228
Tiivistelmä
Abstract
Digital twins for performance-oriented applications in industrial environments require systematic model maintenance. Model adaptation requires efficient optimization tools and continuous evaluation of measurement quality. The adaptation and model performance evaluation are based on the modeling error, making the adaptation prone also to the measurement errors. In this paper, a framework for combining model adaptation and measurement quality assurance are discussed. Two examples with simulated industrialscale biopharmaceutical penicillin fermentation are presented to illustrate the usability of the framework.
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