Tool wear monitoring in ultrasonic welding using high-order decomposition

Yaser Zerehsaz (), Chenhui Shao and Jionghua Jin
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Yaser Zerehsaz: University of Michigan
Chenhui Shao: University of Illinois at Urbana-Champaign
Jionghua Jin: University of Michigan

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 2, No 12, 657-669

Abstract: 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.

Keywords: Ultrasonic metal welding; Tool wear monitoring; High-order representation; Principal component analysis (PCA); High-order singular value decomposition (HOSVD) (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10845-016-1272-4

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