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Semantic Rule-Based Equipment Diagnostics

  • Gulnar MehdiEmail author
  • E. Kharlamov
  • Ognjen Savković
  • G. Xiao
  • E. Güzel Kalaycı
  • S. Brandt
  • I. Horrocks
  • Mikhail Roshchin
  • Thomas Runkler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10588)

Abstract

Industrial rule-based diagnostic systems are often data-dependant in the sense that they rely on specific characteristics of individual pieces of equipment. This dependence poses significant challenges in rule authoring, reuse, and maintenance by engineers. In this work we address these problems by relying on Ontology-Based Data Access: we use ontologies to mediate the equipment and the rules. We propose a semantic rule language, sigRL, where sensor signals are first class citizens. Our language offers a balance of expressive power, usability, and efficiency: it captures most of Siemens data-driven diagnostic rules, significantly simplifies authoring of diagnostic tasks, and allows to efficiently rewrite semantic rules from ontologies to data and execute over data. We implemented our approach in a semantic diagnostic system, deployed it in Siemens, and conducted experiments to demonstrate both usability and efficiency.

Notes

Acknowledgements

This research is supported: EPSRC projects MaSI\(^3\), DBOnto, ED\(^3\); and the Free University of Bozen-Bolzano project QUEST.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Gulnar Mehdi
    • 1
    • 2
    Email author
  • E. Kharlamov
    • 3
  • Ognjen Savković
    • 4
  • G. Xiao
    • 4
  • E. Güzel Kalaycı
    • 4
  • S. Brandt
    • 1
  • I. Horrocks
    • 3
  • Mikhail Roshchin
    • 1
  • Thomas Runkler
    • 1
    • 2
  1. 1.Siemens CTMunichGermany
  2. 2.Technical University of MunichMunichGermany
  3. 3.University of OxfordOxfordUK
  4. 4.Free University of Bozen-BolzanoBolzanoItaly

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