At present, most of the existing traditional AOI detection equipment in the market does not have AI deep learning function, and generally has pain points such as high false alarm rate, which cannot achieve automated production and low production efficiency. The AI artificial intelligence system communicates with friendly AOI devices through the network, and based on the detection results of friendly AOI devices, uses a deep learning based AI artificial intelligence system for re evaluation to reduce false alarm rates and improve detection accuracy.

The particle count re evaluation system is used to analyze the detection report data (particle count) of friendly particle indentation inspection machines. For products with particle counts less than the set threshold, traditional image algorithms and AI deep learning systems are used for secondary re evaluation, greatly improving the detection accuracy. The real NG data is uploaded through CIM and locked.