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Concept for Predicting Vibrations in Machine Tools Using Machine Learning

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Production at the leading edge of technology (WGP 2020)

Part of the book series: Lecture Notes in Production Engineering ((LNPE))

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Abstract

Vibrations have a significant influence on quality and costs in metal cutting processes. Existing methods for predicting vibrations in machine tools enable an informed choice of process settings, however they rely on costly equipment and specialised staff. Therefore, this contribution proposes to reduce the modelling effort required by using machine learning based on data gathered during production. The approach relies on two sub-models, representing the machine structure and machining process respectively. A method is proposed for initialising and updating the models in production.

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Authors and Affiliations

  1. wbk Institute of Production Science, Karlsruhe Institute of Technology (KIT), Kaiserstraße 12, 76131, Karlsruhe, Germany

    D. Barton

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  1. D. Barton
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  2. J. Fleischer
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Correspondence to D. Barton .

Editor information

Editors and Affiliations

  1. Institute of Forming Technology and Machines, Garbsen, Germany

    Bernd-Arno Behrens

  2. Institute of Manufacturing Science and Engineering, Dresden, Germany

    Alexander Brosius

  3. Institute of Production Management and Technology, Hamburg, Germany

    Wolfgang Hintze

  4. Institute of Mechatronic Engineering, Dresden, Germany

    Steffen Ihlenfeldt

  5. Laboratorium for Manufacturing Technology, Hamburg, Germany

    Jens Peter Wulfsberg

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Barton, D., Fleischer, J. (2021). Concept for Predicting Vibrations in Machine Tools Using Machine Learning. In: Behrens, BA., Brosius, A., Hintze, W., Ihlenfeldt, S., Wulfsberg, J.P. (eds) Production at the leading edge of technology. WGP 2020. Lecture Notes in Production Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62138-7_55

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  • DOI: https://doi.org/10.1007/978-3-662-62138-7_55

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-62137-0

  • Online ISBN: 978-3-662-62138-7

  • eBook Packages: EngineeringEngineering (R0)

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