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Tool wear monitoring in ultrasonic welding using high-order decomposition

Author

Listed:
  • Yaser Zerehsaz

    (University of Michigan)

  • Chenhui Shao

    (University of Illinois at Urbana-Champaign)

  • Jionghua Jin

    (University of Michigan)

Abstract

Ultrasonic welding has been used for joining lithium-ion battery cells in electric vehicle manufacturing. The geometric profile change of tool shape significantly affects the weld quality and should be monitored during production. In this paper, a high-order decomposition method is suggested for tool wear monitoring. In the proposed monitoring scheme, a low dimensional set of monitoring features is extracted from the high dimensional tool profile measurement data for detecting tool wear at an early stage. Furthermore, the proposed method can be effectively used to analyze the data cross-correlation structure in order to help identify the unusual wear pattern and find the associated assignable cause. The effectiveness of the proposed monitoring method was demonstrated using a simulation and a real-world case study.

Suggested Citation

  • Yaser Zerehsaz & Chenhui Shao & Jionghua Jin, 2019. "Tool wear monitoring in ultrasonic welding using high-order decomposition," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 657-669, February.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:2:d:10.1007_s10845-016-1272-4
    DOI: 10.1007/s10845-016-1272-4
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    References listed on IDEAS

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    1. Kamran Paynabar & Jionghua Jin & Massimo Pacella, 2013. "Monitoring and diagnosis of multichannel nonlinear profile variations using uncorrelated multilinear principal component analysis," IISE Transactions, Taylor & Francis Journals, vol. 45(11), pages 1235-1247.
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