AI-Assisted Framework for Real-Time Monitoring and Management of Probe Cards in Electrical Wafer Sort Applications

Probe cards are essential components in semiconductor manufacturing, acting as the electrical interface between wafers and automated test equipment during wafer probing. As integrated circuit dimensions continue to shrink, probe cards have become increasingly complex, introducing challenges in design, production, and maintenance. This paper presents a framework for real-time monitoring and management of probe cards in Electrical Wafer Sort applications. By analyzing eight months of historical failure data, we prioritize critical failure modes and identify associated challenges. We propose a sensor network system designed to collect operational data in real-time, enabling future development of machine learning models for anomaly detection and predictive maintenance. This framework aims to enhance probe card reliability and efficiency, leading to improved performance and reduced costs in Electrical Wafer Sort applications.