Using ontologies for representing classifications of an information flow based matching framework for smart manufacturing

Andreas Bildstein, Junkang Feng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We propose a matching framework, which is based on a novel application of the theory of Information Flow and its components, to support the production system on the decision making process on which equipment should be used to conduct a specific production step. This decision making process is part of an application scenario, which is derived from the Industrie 4.0 concept that says that products, production equipment, and production IT systems are getting more and more interconnected to finally reach a certain level of self-organization and autonomy. One of the core components of the proposed IF matching framework is a structure that is called classification. We show within this paper that the traditional approaches of using and representing those classifications with the help of simple table structures cannot be used within our application scenario satisfactorily and discuss how ontologies can be developed and used instead.
Original languageEnglish
Title of host publicationConference Proceedings ICE/IEEE ITMC 2018
PublisherIEEE
Number of pages8
ISBN (Electronic)9781538614693
ISBN (Print)9781538614709
DOIs
Publication statusPublished - 17 Jun 2018
EventInternational Conference on Engineering, Technology and Innovation 2018: Era of Connectedness: The Future of Technology, Engineering & Innovation in a Digital Society - Hospitalhof Stuttgart, Stuttgart, Germany
Duration: 17 Jun 201820 Jun 2018
http://www.ice-conference.org/Home.aspx (Conference website)

Conference

ConferenceInternational Conference on Engineering, Technology and Innovation 2018
Abbreviated titleICE/IEEE ITMC Conference 2018
CountryGermany
CityStuttgart
Period17/06/1820/06/18
Internet address

Keywords

  • ontologies
  • smart manufacturing

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