Digital twins of production lines do not focus solely on the management of the production process, they can also monitor and optimize other extra-functional aspects such as energy consumption and communications. This paper proposes the extension of digital twin concept in such directions. First, we extend the digital twin with models of energy consumption, that allow the monitoring of production line components throughout production lifetime. Then, we propose a flow to design the communication network starting from information obtained from the digital twin concerning the production, usage and flowing of information through the plant. All these methodologies start from the production line specification, then they enrich it with data collected during operation, and finally information is used to perform design and optimization. Results have been shown on a real Industry 4.0 research facility.
Digital Twin Extension with Extra-Functional Properties / Alamin, K.; Vinco, S.; Poncino, M.; Dall’Ora, N.; Fraccaroli, E.; Quaglia, D.. - ELETTRONICO. - (2021), pp. 434-439. (Intervento presentato al convegno Design Automation in Europe (DATE) Conference tenutosi a Virtual nel 01-05 February 2021) [10.23919/DATE51398.2021.9474220].
Digital Twin Extension with Extra-Functional Properties
K. Alamin;S. Vinco;M. Poncino;D. Quaglia
2021
Abstract
Digital twins of production lines do not focus solely on the management of the production process, they can also monitor and optimize other extra-functional aspects such as energy consumption and communications. This paper proposes the extension of digital twin concept in such directions. First, we extend the digital twin with models of energy consumption, that allow the monitoring of production line components throughout production lifetime. Then, we propose a flow to design the communication network starting from information obtained from the digital twin concerning the production, usage and flowing of information through the plant. All these methodologies start from the production line specification, then they enrich it with data collected during operation, and finally information is used to perform design and optimization. Results have been shown on a real Industry 4.0 research facility.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2907664