Context-sensitive optimisation of the key performance indicators for FMS

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.