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Bridging the Gap Between Domain Ontologies for Predictive Maintenance with Machine Learning

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Trends and Applications in Information Systems and Technologies (WorldCIST 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1366))

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Abstract

Predictive maintenance often relies on the continuous monitorization of equipment behavior, generally provided by sensors or by the very equipment. Additional data from management software, including which materials are being used and what processes are executed on the equipment can be used to enrich the data streams and ontologies can be used to bridge the gap between these different domains, while also facilitating the comprehension of the results obtained by the analytic methods applied to the data. Existing ontologies model these problems independently, and a holistic view that takes in consideration the temporal requirements of predictive maintenance is not yet available. This paper analysis existing ontologies and proposes a number of extensions that bridge the gaps between them, while meeting the time-sensitive requirements of the problem.

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Acknowledgements

The present work has been developed under the EUREKA - ITEA3 Project PIANISM (Itea-17008), PIANISM (ANI|P2020 40125). Alda Canito is supported by national funds through FCT – Fundação para a Ciência e Tecnologia through project UIDB/00760/2020 and Ph.D scholarship with reference SFRH/BD/147386/2019.

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Authors and Affiliations

  1. GECAD - Research Group On Intelligent Engineering and Computing for Advanced, Innovation and Development, Institute of Engineering - Polytechnic of Porto, Porto, Portugal

    Alda Canito & Goreti Marreiros

  2. Department of Computer Science, University of Salamanca, Salamanca, Spain

    Juan Corchado

Authors
  1. Alda Canito
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  2. Juan Corchado
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  3. Goreti Marreiros
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Corresponding author

Correspondence to Alda Canito .

Editor information

Editors and Affiliations

  1. ISEG, University of Lisbon, Lisbon, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. Department of Information Sciences, University of Sheffield, Lisbon, Portugal

    Ana Maria Ramalho Correia

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Canito, A., Corchado, J., Marreiros, G. (2021). Bridging the Gap Between Domain Ontologies for Predictive Maintenance with Machine Learning. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1366. Springer, Cham. https://doi.org/10.1007/978-3-030-72651-5_51

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