Tool Wear Monitoring for Ultrasonic Metal Welding of Lithium-Ion Batteries

Chenhui Shao, Tae Hyung Kim, S. Jack Hu, Jionghua Jin, Jeffrey A. Abell, J. Patrick Spicer

Research output: Contribution to journalArticlepeer-review


This paper presents a tool wear monitoring framework for ultrasonic metal welding which has been used for lithium-ion battery manufacturing. Tool wear has a significant impact on joining quality. In addition, tool replacement, including horns and anvils, constitutes an important part of production costs. Therefore, a tool condition monitoring (TCM) system is highly desirable for ultrasonic metal welding. However, it is very challenging to develop a TCM system due to the complexity of tool surface geometry and a lack of thorough understanding on the wear mechanism. Here, we first characterize tool wear progression by comparing surface measurements obtained at different stages of tool wear, and then develop a monitoring algorithm using a quadratic classifier and features that are extracted from space and frequency domains of cross-sectional profiles on tool surfaces. The developed algorithm is validated using tool measurement data from a battery plant.

Original languageEnglish (US)
Article number051005
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Issue number5
StatePublished - May 1 2016
Externally publishedYes


  • electric vehicles
  • lithium-ion batteries
  • tool wear monitoring
  • ultrasonic metal welding

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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