From Reactive to Predictive: AI-Driven Optimization for ATE Performance & Reliability


As ATE systems become increasingly complex and data-intensive, traditional rule-based optimization methods struggle to keep pace. In this Semicon Korea presentation, Cohu's Wai-Kong Chen will be exploring how artificial intelligence enables a paradigm shift from reactive troubleshooting to predictive and self-optimizing ATE systems. Read more here. Fig.1: Sweet spot inference.  Sourc... » read more

Weaving Digital Threads Into A Global Fabric Of Enterprise Knowledge


How smart manufacturing software provides visibility and control of all phases of the semiconductor manufacturing process. Run-to-run (R2R) automated process control gathers critical data from each production run and automatically adjusts process parameters for the next run based on sophisticated models of process performance. Click here to read more. » read more