Monitoring and Automating Factories Using Semantic Models

  • Niklas Petersen
  • Michael Galkin
  • Christoph Lange
  • Steffen Lohmann
  • Sören Auer
Conference paper

DOI: 10.1007/978-3-319-50112-3_24

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10055)
Cite this paper as:
Petersen N., Galkin M., Lange C., Lohmann S., Auer S. (2016) Monitoring and Automating Factories Using Semantic Models. In: Li YF. et al. (eds) Semantic Technology. JIST 2016. Lecture Notes in Computer Science, vol 10055. Springer, Cham

Abstract

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.

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Niklas Petersen
    • 1
    • 2
  • Michael Galkin
    • 1
    • 2
    • 3
  • Christoph Lange
    • 1
    • 2
  • Steffen Lohmann
    • 2
  • Sören Auer
    • 1
    • 2
  1. 1.University of BonnBonnGermany
  2. 2.Fraunhofer IAISSankt AugustinGermany
  3. 3.ITMO UniversitySaint PetersburgRussia

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