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

[+] Author Affiliations
Chenhui Shao, Tae Hyung Kim, S. Jack Hu, Jionghua (Judy) Jin

University of Michigan, Ann Arbor, MI

Jeffrey A. Abell, J. Patrick Spicer

General Motors Technical Center, Warren, MI

Paper No. MSEC2015-9428, pp. V002T05A022; 9 pages
  • ASME 2015 International Manufacturing Science and Engineering Conference
  • Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
  • Charlotte, North Carolina, USA, June 8–12, 2015
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5683-3
  • Copyright © 2015 by ASME and General Motors


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 tool condition classification algorithm to identify the state of wear. The developed algorithm is validated using tool measurement data from a battery plant.

Copyright © 2015 by ASME and General Motors



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