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A Retrofit Approach for Predictive Maintenance

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Tagungsband des 4. Kongresses Montage Handhabung Industrieroboter

Zusammenfassung

New technologies are driving the advancing digitalization of both consumer and industrial environments. Especially in maintenance, new possibilities to predict malfunctions and failures arise by real-time analytics of relevant data streams. In the context of this paper, the development and implementation of a predictive maintenance system based on low-cost embedded systems and sensor technology from the consumer sector will be presented. This includes the implementation of the device, its connection to the Internet of Things (IoT) as well as the application of machine learning. The system developed will be demonstrated at a robotic cell at the Institute of Production Systems (IPS).

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Author information

Authors and Affiliations

  1. Institute of Production Systems, TU Dortmund University, Dortmund, Deutschland

    René Wöstmann, André Barthelmey, Nikolai West & Jochen Deuse

Authors
  1. René Wöstmann
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  2. André Barthelmey
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  3. Nikolai West
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  4. Jochen Deuse
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Corresponding author

Correspondence to René Wöstmann .

Editor information

Editors and Affiliations

  1. TU Hamburg, Hamburg, Germany

    Thorsten Schüppstuhl

  2. Universität Bremen, Bremen, Germany

    Kirsten Tracht

  3. RWTH Aachen, Aachen, Germany

    Jürgen Roßmann

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© 2019 Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature

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Wöstmann, R., Barthelmey, A., West, N., Deuse, J. (2019). A Retrofit Approach for Predictive Maintenance. In: Schüppstuhl, T., Tracht, K., Roßmann, J. (eds) Tagungsband des 4. Kongresses Montage Handhabung Industrieroboter. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59317-2_10

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  • DOI: https://doi.org/10.1007/978-3-662-59317-2_10

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  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-59316-5

  • Online ISBN: 978-3-662-59317-2

  • eBook Packages: Computer Science and Engineering (German Language)

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