Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1697385 | Journal of Manufacturing Systems | 2016 | 10 Pages |
Abstract
Ultrasonic metal welding is used for joining lithium-ion batteries of electric vehicles. The monitoring of battery joining processes requires near-zero misdetection in order to prevent any battery joints with a low quality connection going into the downstream assembly. The conventional control chart techniques widely used in many process monitoring systems were designed based on a pre-specified false alarm rate. To ensure weld quality and reduce manual inspection at the same time, a near-zero misdetection rate is desired foremost while achieving a low false alarm rate. A monitoring algorithm targeting near-zero misdetection is developed in this article by integrating univariate control charts and the Mahalanobis distance approach. The proposed algorithm is capable of monitoring non-normal multivariate observations with flexible control limits to achieve a near-zero misdetection rate while keeping a low false alarm rate. By implementing this algorithm on the ultrasonic welding process of battery manufacturing, the developed algorithm proves to be effective in achieving near-zero misdetection in process monitoring to ensure battery weld quality. The developed algorithm also shows great potential for monitoring other processes that target at near-zero misdetection.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Weihong Guo, Chenhui Shao, Tae Hyung Kim, S. Jack Hu, Jionghua (Judy) Jin, J. Patrick Spicer, Hui Wang,