Abstract
Many initiatives aim at describing the objectives and functionalities of the so-called digital twin of manufacturing systems. Considering the assets, the twin is meant to be able to both exhibit the actual and current states of the resources, and provide some estimates about the future behaviour of these resources. To target the sustainability pillar of future industrial systems, the energy monitoring and management are critical issues. Consequently, the integration of multi-physics models helping to model the resources inside the twin is a major issue to deal with. This article introduces a framework integrating the models inside the twin of the ARTI architecture, proposes a methodology to implement the twin on a resource and illustrates these ideas in a case study on injection moulding machines.
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Cardin, O. et al. (2020). Energy-Aware Resources in Digital Twin: The Case of Injection Moulding Machines. In: Borangiu, T., Trentesaux, D., Leitão, P., Giret Boggino, A., Botti, V. (eds) Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future. SOHOMA 2019. Studies in Computational Intelligence, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-030-27477-1_14
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DOI: https://doi.org/10.1007/978-3-030-27477-1_14
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