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Predicting the Vibroacoustic Quality of Steering Gears

In: Operations Research Proceedings 2018

Author

Listed:
  • Paul Alexandru Bucur

    (Alpen-Adria-Universität Klagenfurt)

  • Klaus Frick

    (Institute of Computational Engineering, NTB Interstate University of Technology Buchs)

  • Philipp Hungerländer

    (Alpen-Adria-Universität Klagenfurt)

Abstract

In the daily operations of ThyssenKrupp Presta AG, ball nut assemblies (BNA) undergo a vibroacoustical quality test and are binary classified based on their order spectra. In this work we formulate a multiple change point problem and derive optimized quality intervals and thresholds for the order spectra that minimize the number of incorrectly classified BNA. We pursue a multiobjective goal: the first objective function maximizes the Cohen Kappa metric, while the second objective function reduces the number of employed order intervals. The proposed approach is based on a genetic algorithm and incorporates prior information on the correlation structure of BNA and steering gear vibroacoustics, gained via canonical correlation analysis. The computational experiments show a reduction of both the number of employed order intervals and the costs arising from falsely classified BNA parts with respect to the current production setting, ensuring thus a high practical relevance of our suggested approach.

Suggested Citation

  • Paul Alexandru Bucur & Klaus Frick & Philipp Hungerländer, 2019. "Predicting the Vibroacoustic Quality of Steering Gears," Operations Research Proceedings, in: Bernard Fortz & Martine Labbé (ed.), Operations Research Proceedings 2018, pages 309-315, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-18500-8_39
    DOI: 10.1007/978-3-030-18500-8_39
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