Semantic CPPS in Industry 4.0

• URL: http://arxiv.org/abs/2011.11395v1
• Date: Wed, 18 Nov 2020 21:53:07 GMT
• Title: Semantic CPPS in Industry 4.0
• Authors: Giuseppe Fenza and Mariacristina Gallo and Vincenzo Loia and Domenico Marinoand Francesco Orciuoli and Alberto Volpe
• Abstract summary: Cyber-Physical Systems (CPS) play a crucial role in the era of the 4thIndustrial Revolution. Semantic Web standards and technologies may have a promising role to represent manufacturing knowledge in a machine-interpretable way. This paper proposes an integration of Semantic Web models for implementing the a5C architecture mainly targeted to collect and process semantic data stream.
• Score: 3.094458292166017
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Cyber-Physical Systems (CPS) play a crucial role in the era of the 4thIndustrial 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 theIndustry 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 a5C 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 datastream. Then, C-SPARQL queries are defined for periodically carrying out useful KPIs to address the proposed aim.

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