Ontology-based reasoning to reconFigure industrial processes for energy efficiency

Modern factories collect and process a large volume of different types of industrial process data. These data are used to develop metrics and Key Performance Indicators to monitor and improve productivity and the efficiency of a factory. Improving the efficiency of an industrial process, however, Th...

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Bibliographic Details
Main Authors: Kouzapas, Dimitrios, Stylianidis, Nearchos, Panayiotou, Christos G., Eliades, Demetrios G.
Format: Conference Proceeding
Language:English
Subjects:
Automation
Decision support systems
Energy efficiency
Key performance indicator
Process control
Production facilities
Productivity
Online Access:Request full text
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Summary:Modern factories collect and process a large volume of different types of industrial process data. These data are used to develop metrics and Key Performance Indicators to monitor and improve productivity and the efficiency of a factory. Improving the efficiency of an industrial process, however, This work develops an ontology-based framework that semantically describes an industrial process, and in particular it describes the elements of physical connectivity, industrial behaviour, and KPIs. Using a notion of sub-process hierarchy, a Decision Support System explores and suggests options for reconfiguring the elements of the industrial process, to improve efficiency. A proof-of-concept use-case from the KIOS Water System Testbed is presented. The pumping station (connectivity, behaviour and energy efficiency KPIs) of the Testbed is semantically modelled, whereas the DSS suggests reconfiguration options for improving its overall energy efficiency.
ISSN:2473-3504
DOI:10.1109/MED59994.2023.10185805