Federated Transfer Learning with Task Personalization for Condition Monitoring in Ultrasonic Metal Welding

arXiv:2404.13278v1 Announce Type: new
Abstract: Ultrasonic metal welding (UMW) is a key joining technology with widespread industrial applications. Condition monitoring (CM) capabilities are critically needed in UMW applications because process anomalies significantly deteriorate the joining quality. Recently, machine learning models emerged as a promising tool for CM in many manufacturing applications due to their ability to learn complex patterns. Yet, the successful deployment of these models requires substantial training data that may be expensive and time-consuming to collect. Additionally, many …

abstract applications arxiv capabilities cs.ai cs.dc cs.lg eess.sp industrial key machine machine learning machine learning models metal monitoring personalization process quality technology tool transfer transfer learning type