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Das Internet of Production als Fundament der Datenverwertung in der Produktion

Herausforderungen und Lösungsansätze des datengetriebenen Erkenntnisgewinns

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Monetarisierung von technischen Daten

Zusammenfassung

Das Internet of Things entfaltet erst durch die Überwindung von bestehenden Produkt- und Industriegrenzen sein volles ökonomisches Potenzial. Trotzdem werden Cyberphysische Systeme in der Forschung bisher oftmals isoliert betrachtet. Der Begriff des Internet of Production (IoP) steht für die Vision eines übergreifenden Austauschs von Daten und Informationen zwischen Produktentwicklung, Produktion und Nutzungsphase – über bestehende Organisationsgrenzen hinaus. Die Realisierung des IoP ist mit Herausforderungen im Bereich der datengetriebenen Modellierung sowie der Infrastruktur verbunden. In diesem Buchbeitrag werden die bestehenden Herausforderungen erläutert und Lösungsansätze skizziert. Der Schwerpunkt liegt auf der datengetriebenen Modellierung. Im Speziellen wird die Problematik des Lernens von kausalen Zusammenhängen, die Interpretierbarkeit von Machine-Learning-Modellen sowie die Integration von Domänenwissen in Lernalgorithmen diskutiert. Abschließend werden zwei Anwendungsbeispiele des „Digital Material Shadows“ vorgestellt. Diese veranschaulichen wie mithilfe von Machine Learning Erkenntnisse über den Materialzustand eines Werkstücks gewonnen werden können. Ziel dieser Digital Material Shadows ist es, langfristig Fertigungsprozesse adaptiv an die individuellen Materialeigenschaften des vorliegenden Werkstücks bzw. Rohmaterials anzupassen.

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Danksagung

Die Autoren bedanken sich für die Förderung durch die Deutsche Forschungsgemeinschaft (DFG) im Rahmen der Exzellenzstrategie des Bundes und der Länder – EXC-2023 Internet of Production – 390621612.

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Authors and Affiliations

  1. Werkzeugmaschinenlabor WZL der RWTH Aachen, RWTH Aachen University, Aachen, Deutschland

    Marco Becker, Philipp Niemietz, Daniel Trauth, Thomas Bergs & Christian Brecher

  2. Exzellenzcluster Internet of Production (IoP), RWTH Aachen University, Aachen, Deutschland

    Matthias Brockmann

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  1. Marco Becker
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Correspondence to Marco Becker .

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Editors and Affiliations

  1. Senseering GmbH, Köln, Nordrhein-Westfalen, Deutschland

    Daniel Trauth

  2. Lehrstuhl für Technologie der Fertigungsverfahren, Werkzeugmaschinenlabor WZL der RWTH Aachen, Aachen, Nordrhein-Westfalen, Deutschland

    Thomas Bergs

  3. Fraunhofer-Institut für Angewandte Informationstechnik FIT, Sankt Augustin, Nordrhein-Westfalen, Deutschland

    Wolfgang Prinz

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Becker, M., Brockmann, M., Niemietz, P., Trauth, D., Bergs, T., Brecher, C. (2021). Das Internet of Production als Fundament der Datenverwertung in der Produktion. In: Trauth, D., Bergs, T., Prinz, W. (eds) Monetarisierung von technischen Daten. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62915-4_15

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