In the electronics/PCBA industry, the quality of gold fingers directly affects product performance. DaoAI provides an efficient solution for gold finger scratch and oxidation inspection with advanced AI vision technology.
User Scenario: A leading electronics/PCBA manufacturer's SMT production line is mainly engaged in producing various circuit board products. During the production process, it is necessary to inspect the gold fingers on the circuit boards for scratches and oxidation. As the key part for the circuit board to connect with other devices, the surface quality of the gold fingers is crucial. Any scratches or oxidation may lead to unstable signal transmission and affect the overall performance of the product.
Pain Points: Traditional automatic optical inspection (AOI) equipment faces many difficulties in the inspection of gold finger scratches and oxidation. On the one hand, it is greatly affected by ambient light. Different lighting conditions can cause significant differences in image acquisition results, thus increasing the false alarm rate. Statistics show that the false alarm rate of traditional AOI equipment is as high as 30%. This means that a large number of qualified products are misjudged as defective and need to be re - inspected, which greatly increases labor costs and inspection time. On the other hand, limited by rules, traditional AOI equipment is prone to miss some complex scratches and slight oxidation phenomena, with a miss - detection rate of about 5%, which poses a potential threat to product quality.
Technical Principles
DaoAI uses advanced deep - learning algorithms and self - developed 3D camera imaging technology to solve the gold finger inspection problem. Deep - learning algorithms have powerful feature - learning capabilities and can automatically learn the feature patterns of gold finger scratches and oxidation from a large amount of image data. By training on images under different lighting conditions, the algorithm can adaptively adjust the feature extraction strategy to reduce the influence of ambient light. The self - developed 3D camera can obtain the three - dimensional topography information of the gold fingers. Through the three - dimensional topography reconstruction technology, the subtle changes on the surface of the gold fingers can be clearly presented. For defects such as scratches and oxidation, there will be obvious characteristic manifestations in the three - dimensional topography, such as height changes and surface roughness changes. By analyzing and identifying these three - dimensional features, the defects of the gold fingers can be detected more accurately, effectively avoiding miss - detection and false alarms.
- The deep - learning algorithm learns the feature patterns of gold finger defects through a large amount of data training to improve the detection accuracy.
- The 3D camera obtains the three - dimensional topography information of the gold fingers, and the three - dimensional topography reconstruction technology clearly presents the subtle surface changes.
- By analyzing three - dimensional features such as height changes and surface roughness changes, scratches and oxidation defects can be accurately identified.
- The feature extraction strategy is adaptively adjusted to reduce the influence of ambient light on the detection results.
DaoAI's Solutions and Product Introduction
DaoAI provides a combined solution of the DaoAI AI AOI software system and the DaoAI 2D / 3D AI AOI equipment. The DaoAI AI AOI software system is based on the feature recognition of the visual basic model and has the ability of rapid programming. Only 5 minutes are needed to complete the 0 - code automatic programming for a good product. At the same time, using the APDT positive - sample/few - sample learning technology, it can quickly learn the normal features of the gold fingers with only 1 - 20 good product images, realizing efficient model training. In addition, the software system also has a semantic false - alarm filtering function, which can effectively reduce false alarms. The DaoAI 2D / 3D AI AOI equipment is equipped with a self - developed 3D camera and can perform three - dimensional topography reconstruction, which can detect hidden solder joints, coplanarity, and micron - level topography, providing high - precision hardware support for the inspection of gold finger scratches and oxidation. In the implementation process, the equipment is first installed and debugged to ensure its stable operation. Then, the DaoAI AI AOI software system is used for model training, and the parameters are adjusted according to the actual production situation to optimize the detection effect. Finally, the trained model is deployed on the equipment to achieve real - time detection of the gold fingers.
DaoAI's solution provides reliable guarantee for gold finger inspection through advanced software systems and high - precision hardware equipment.
Quantitative Results: By adopting DaoAI's solution, the leading electronics/PCBA manufacturer has achieved remarkable results. The detection rate of gold finger scratches and oxidation has increased from the original 95% to 98%, effectively reducing the miss - detection rate. At the same time, the false alarm rate has been significantly reduced from 30% to 8%, and the re - inspection volume has been reduced by 70%, greatly improving the inspection efficiency and reducing labor costs. In addition, the change - over time has been shortened from the original 30 minutes to 5 minutes, improving the flexibility and production efficiency of the production line.