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Datenanalyse in der intelligenten Fabrik

Handbuch Industrie 4.0

Part of the book series: Springer NachschlageWissen

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Zusammenfassung

Die Mehrheit der Projekte zur Überwachung und Diagnose cyber-physischer Systeme (CPS) beruht auf von (menschlichen) Experten erstellten Modellen. Diese Modelle sind jedoch nur selten verfügbar, sind oft unvollständig, schwer zu überprüfen und zu warten. Datengetriebene Ansätze sind eine viel versprechende Alternative: Diese nutzen die großen Datenmengen die heutzutage in CPS gesammelt werden. Algorithmen verwenden die Daten, um die zur Überwachung notwendigen Modelle automatisch zu lernen. Dabei sind mehrere Herausforderungen zu bewältigen, wie zum Beispiel die Echtzeit-Datenerfassung und Speicherung, Datenanalyse, Mensch-Maschine Schnittstellen, Feedback- und Steuerungsmechanismen. In diesem Beitrag wird eine kognitive Referenzarchitektur vorgeschlagen um diese Herausforderungen in Zukunft einfacher zu lösen. Diese soll durch die Bereitstellung eines Vergleichsschemas sowohl die Wiederverwendung von Algorithmen erleichtern, als auch den wissenschaftlichen Diskurs unterstützen. Anwendungsfälle aus unterschiedlichen Branchen werden schematisch dargestellt und untermauern die Richtigkeit und den Nutzen der Architektur.

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Authors and Affiliations

  1. Fraunhofer-Anwendungszentrum Industrial Automation, Lemgo, Deutschland

    Oliver Niggemann & Sören Volgmann

  2. Vanderbilt University und Institute for Software Integrated Systems, Nashville, TN, USA

    Gautam Biswas, John S. Kinnebrew & Hamed Khorasgani

  3. Institut für Industrielle Informationstechnik inIT, Lemgo, Deutschland

    Andreas Bunte

Authors
  1. Oliver Niggemann
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  2. Gautam Biswas
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  3. John S. Kinnebrew
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  4. Hamed Khorasgani
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  5. Sören Volgmann
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  6. Andreas Bunte
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Correspondence to Oliver Niggemann .

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Editors and Affiliations

  1. Garching, Bayern, Germany

    Birgit Vogel-Heuser

  2. Stuttgart, Baden-Württemberg, Germany

    Thomas Bauernhansl

  3. Dortmund, Nordrhein-Westfalen, Germany

    Michael ten Hompel

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Niggemann, O., Biswas, G., Kinnebrew, J.S., Khorasgani, H., Volgmann, S., Bunte, A. (2016). Datenanalyse in der intelligenten Fabrik. In: Vogel-Heuser, B., Bauernhansl, T., ten Hompel, M. (eds) Handbuch Industrie 4.0. Springer NachschlageWissen(). Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45537-1_73-1

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  • DOI: https://doi.org/10.1007/978-3-662-45537-1_73-1

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Chapter history

  1. Latest

    als Kernfrage des Maschinellen Lernens in der Produktion
    Published:
    27 February 2020

    DOI: https://doi.org/10.1007/978-3-662-45537-1_73-2

  2. Original

    Datenanalyse in der intelligenten Fabrik
    Published:
    20 May 2016

    DOI: https://doi.org/10.1007/978-3-662-45537-1_73-1

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