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Monitoring and automating factories using semantic models

: Petersen, N.; Galkin, M.; Lange, C.; Lohmann, S.; Auer, S.


Li, Y.-F.:
Semantic technology. 6th joint international conference, JIST 2016 : Singapore, Singapore, November 2-4, 2016; Revised, selected papers
Cham: Springer International Publishing, 2016 (Lecture Notes in Computer Science 10055)
ISBN: 978-3-319-50111-6 (Print)
ISBN: 978-3-319-50112-3 (Online)
Joint International Semantic Technology Conference (JIST) <6, 2016, Singapore>
Conference Paper
Fraunhofer IAIS ()

Keeping factories running at any time is a critical task for every manufacturing enterprise. Optimizing the flows of goods and services inside and between factories is a challenge that attracts much attention in research and business. The idea to fully describe a factory in a digital form to improve decision making is called a virtual factory. While promising virtual factory frameworks have been proposed, their semantic models lack depth and suffer from limited expressiveness. We propose an enhanced semantic model of a factory, which enables views spanning from the high level of supply chains to the low level of machines on the shop floor. The model includes a mapping to relational production databases to support federated queries on different legacy systems in use. We evaluate the model in a production line use case, demonstrating that it can be used for typical factory tasks, such as assembly line identification or machine availability checks.