Finding anomalies and defects faster in complex chip and package topographies.
AI is exceptionally good at spotting anomalies in semiconductor inspection. The challenge is training different models for different inspection tools and topographies, and knowing which model to use at any particular time. Different textures in backgrounds are difficult for traditional algorithms, for example. But once machine learning models are trained properly, they have proven effective in identifying real and potential defects. The same is true for PCB segmentation. Charlie Zhu, vice president of research and development at Nordson Test & Inspection, talks about how AI is used in different types of inspection today, how it may be used in the future, and where it works best.
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