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.

Classify defects detected by friendly AOI equipment using AI for quality traceability. The classification accuracy reaches over 99%.

The bonding foreign object detection system is used to detect foreign objects in the pictures of friendly particle indentation inspection machines. Due to the inability of particle indentation inspection machines to detect defects such as scratches, foreign objects, and fragments, it may miss detection. Our bonding foreign object detection system can detect the above defects and improve the yield rate of the production line.

Production Operation AI Monitoring System   The production operation AI monitoring system (production operation error prevention AI monitoring system) can collect the operation process, the movement trajectory of employees and equipment, identify errors such as missing, wrong, missing, and missing in production operations, including employees' picking actions, movement trajectories, insertion positions, etc., and issue timely alarms. This not only improves production efficiency, but also reduces product quality problems caused by human errors. In addition to real-time monitoring, the system can also monitor the compliance of the production process, retain and audit production related records and data, which is of great significance for the compliance management and risk control of enterprises.