Cyber-Physical Systems (CPS) play a crucial role in the era of the 4th Industrial Revolution. Recently, the application of the CPS to industrial manufacturing leads to a specialization of them referred as Cyber-Physical Production Systems (CPPS). Among other challenges, CPS and CPPS should be able to address interoperability issues, since one of their intrinsic requirement is the capability to interface and cooperate with other systems. On the other hand, to fully realize the Industry 4.0 vision, it is required to address horizontal, vertical, and end-to-end integration enabling a complete awareness through the entire supply chain. In this context, Semantic Web standards and technologies may have a promising role to represent manufacturing knowledge in a machine-interpretable way for enabling communications among heterogeneous Industrial assets. This paper proposes an integration of Semantic Web models available at state of the art for implementing a 5C architecture mainly targeted to collect and process semantic data stream in a way that would unlock the potentiality of data yield in a smart manufacturing environment. The analysis of key industrial ontologies and semantic technologies allows us to instantiate an example scenario for monitoring Overall Equipment Effectiveness (OEE). The solution uses the SOSA ontology for representing the semantic data stream. Then, C-SPARQL queries are defined for periodically carrying out useful KPIs to address the proposed aim.
Semantic CPPS in Industry 4.0
Fenza G.;Gallo M.;Loia V.;Orciuoli F.;Volpe A.
2020-01-01
Abstract
Cyber-Physical Systems (CPS) play a crucial role in the era of the 4th Industrial Revolution. Recently, the application of the CPS to industrial manufacturing leads to a specialization of them referred as Cyber-Physical Production Systems (CPPS). Among other challenges, CPS and CPPS should be able to address interoperability issues, since one of their intrinsic requirement is the capability to interface and cooperate with other systems. On the other hand, to fully realize the Industry 4.0 vision, it is required to address horizontal, vertical, and end-to-end integration enabling a complete awareness through the entire supply chain. In this context, Semantic Web standards and technologies may have a promising role to represent manufacturing knowledge in a machine-interpretable way for enabling communications among heterogeneous Industrial assets. This paper proposes an integration of Semantic Web models available at state of the art for implementing a 5C architecture mainly targeted to collect and process semantic data stream in a way that would unlock the potentiality of data yield in a smart manufacturing environment. The analysis of key industrial ontologies and semantic technologies allows us to instantiate an example scenario for monitoring Overall Equipment Effectiveness (OEE). The solution uses the SOSA ontology for representing the semantic data stream. Then, C-SPARQL queries are defined for periodically carrying out useful KPIs to address the proposed aim.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.