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Context-sensitive optimisation of the key performance indicators for FMS

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This article presents a context-sensitive optimisation approach for flexible manufacturing systems (FMSs), considering dynamic machine utilisation rate and overall equipment effectiveness (OEE) as the key performance indicators (KPIs). Run-time contextual entities are used to monitor KPIs continuously to update an ontology-based context model and subsequently convert it into business-relevant information via context management. The delivered high-level knowledge is further utilised by an optimisation support system (OSS) to infer optimal job (re)scheduling and dispatching, keeping a higher machine utilisation rate at run-time. The reference architecture is presented as add-on functionality for FMS control, where a modular development of the overall approach provides the solution generic and extendable across other domains. The key components are functionally implemented to a practical FMS use-case within service-oriented architecture -based control architecture. Test runs are performed in a simulated environment provided by the use-case control software, and the results are analysed, which indicates an improvement of the dynamic machine utilisation rate and the enhancement of the OEE.
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Keywords: context; flexible manufacturing systems (FMS); key performance indicator (KPI); optimisation; service-oriented architecture (SOA); web ontology language (OWL); web service (WS)

Document Type: Research Article

Affiliations: Department of Production Engineering, Tampere University of Technology, FI-33101, Tampere, Finland

Publication date: September 2, 2015

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