How AI enables a paradigm shift from reactive troubleshooting to predictive and self-optimizing ATE systems.
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.
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Fig.1: Sweet spot inference. Source: Cohu
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