AI inspection systems are powered by Deep Learning and Computer Vision technologies. By training models with large volumes of image data, the system can automatically identify a wide range of solder joint and component defects, such as cold solder, misalignment, short circuits, solder balls, and missing parts. Compared with conventional methods, AI-based inspection offers superior adaptability and self-learning capabilities, maintaining high detection accuracy under varying lighting conditions, viewing angles, and board types—significantly reducing both false positives and missed defects.
In practical applications, AI systems integrate high-resolution industrial cameras, multi-light source imaging, and real-time data analysis to enable in-line inspection and closed-loop quality control. Inspection results can be directly uploaded to MES systems, ensuring full product traceability and process optimization. Through continuous training and data accumulation, the system’s recognition accuracy improves over time, helping factories transition from experience-based decisions to data-driven intelligent manufacturing.
Today, AI-powered inspection has been widely adopted in fields such as consumer electronics, automotive electronics, industrial control, and energy storage systems. It not only enhances inspection efficiency and yield rates but also reduces labor costs—driving the manufacturing process toward a higher level of automation and intelligence.