Paper on Explainable Few-shot Learning for Ultrasonic Metal Welding Published in Journal of Manufacturing Processes

Recently, our paper titled “Explainable few-shot learning for online anomaly detection in ultrasonic metal welding with varying configurations” has been published on Journal of Manufacturing Processes. The paper was co-authored by Yuquan Meng, Kuan-Chieh Lu, Zhiqiao Dong, Shichen Li, and Prof. Chenhui Shao. Modern manufacturing is featured by rapid reconfiguration and agile adaptation that necessitate varying process configurations. In ultrasonic metal welding, a process […]

Papers published at MSEC 2023 and NAMRC 51 conferences

Our PhD students Kuan-Chieh, Zhiqiao, and Manan published papers and present their research at MSEC 2023 & NAMRC 51 at Rutgers University this summer. Kuan-Chieh’s paper titled “Online Cost-Effective Classification of Mixed Tool and Material Conditions in Ultrasonic Metal Welding: Towards Integrated Monitoring and Control” has been published at MSEC 2023. Ultrasonic metal welding (UMW) […]