The use of automation in flexible and reconfigurable manufacturing and assembly systems demands for tools and methodologies to manage human–machine collaboration, in terms of tasks’ optimization, performances and safety requirements. The study of automation in production cells and lines shall consider dynamic working environment and variable operational settings. Mapping this knowledge requires structured approaches, such as ontology models, used as references for knowledge representation and reasoning guidance. In this working paper, we merge an ontology with experimental data to construct a knowledge graph to be used for industrial management. The knowledge graph representation acts as a digital twin of the process, allowing to exploit graph metrics and subsequently develop indicators for guiding systems' tasks’ assignment and adaptation. The proposed solution is related to a case study of a full-scale lab model of an assembly cell.
Simone F., Di Gravio G., Patriarca R., Bortolini M., Galizia F.G., Gamberi M. (2023). Managing Industrial Automation: How Knowledge Graphs Can Boost Production. Cham : Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-34821-1_34].
Managing Industrial Automation: How Knowledge Graphs Can Boost Production
Bortolini M.;Galizia F. G.;Gamberi M.
2023
Abstract
The use of automation in flexible and reconfigurable manufacturing and assembly systems demands for tools and methodologies to manage human–machine collaboration, in terms of tasks’ optimization, performances and safety requirements. The study of automation in production cells and lines shall consider dynamic working environment and variable operational settings. Mapping this knowledge requires structured approaches, such as ontology models, used as references for knowledge representation and reasoning guidance. In this working paper, we merge an ontology with experimental data to construct a knowledge graph to be used for industrial management. The knowledge graph representation acts as a digital twin of the process, allowing to exploit graph metrics and subsequently develop indicators for guiding systems' tasks’ assignment and adaptation. The proposed solution is related to a case study of a full-scale lab model of an assembly cell.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
