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Towards processing and reasoning streams of events in knowledge-driven manufacturing execution systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationIEEE 13th International Conference on Industrial Informatics (INDIN), 2015
Pages1075-1080
Number of pages6
DOIs
Publication statusPublished - 1 Jul 2015
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Industrial Informatics -
Duration: 1 Jan 1900 → …

Conference

ConferenceIEEE International Conference on Industrial Informatics
Period1/01/00 → …

Abstract

The incessant need of the industry to optimize processes due to market demands derived in a huge investment on information communication technologies implementation during last decades, in the industrial automation domain. This caused the implementation of paradigms as service-oriented or event-driven architectures in factories, used for wide data integration. Moreover, the use of knowledge representation, within ontologies, permitted the description of system status in knowledge bases, which can be queried and updated at runtime. Due to the massive occurrence of events at any location of the enterprise, complex event processing (CEP) technologies can be used for anticipating facts that can compromise the production at shop floors. In fact, recent implementations on processing and reasoning streams of events in the Semantic Web can be applied also in the industrial automation domain because they combine CEP and SPARQL, which are technologies nowadays used by factory systems. This article describes how these technologies can support the study of the ontological system models evolution through time and an approach to bring predictability to current knowledge-based systems.

Keywords

  • SQL, factory automation, knowledge based systems, ontologies (artificial intelligence), production engineering computing, semantic Web, service-oriented architecture, CEP technologies, SPARQL, complex event processing, data integration, event processing stream, event reasoning stream, event-driven architectures, industrial automation domain, information communication technology implementation, investment, knowledge representation, knowledge-based systems, knowledge-driven manufacturing execution systems, market demands, ontological system model evolution, ontologies, service-oriented architectures, Automation, Cognition, Manufacturing, Monitoring, Ontologies, Production, Resource description framework, Complex Event Processing, industrial automation, knowledge-based sysems

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