In the electronics/PCBA industry, the inspection of hidden solder joints under BGA/QFN packaging has always been a difficult problem. WeLinkirt provides an effective solution to this problem with advanced AI vision technology.
User scenario: In the production line of a leading electronics/PCBA manufacturer, there is an electronic product production process involving BGA/QFN packaging. Its products are mainly various high-performance circuit boards, and the inspection object is the hidden solder joints under BGA/QFN packaging. Due to their special positions, these hidden solder joints are difficult to reach by traditional inspection methods and have a crucial impact on the quality and stability of the products.
Pain points: In the traditional inspection process, there are many quantitative dilemmas. On the one hand, because the hidden solder joints under BGA/QFN packaging are in a complex structure, the reflective/mirror metal makes the 3D point cloud sparse, noisy and missing, resulting in pose and detection failures. The missed detection rate is as high as 3%, which means that there may be 3 products with hidden solder joint problems in every 100 products that are not detected. On the other hand, the false alarm rate also reaches 15%. A large number of false alarms not only increase the labor cost but also reduce the production efficiency. In addition, the model change time is long, and it takes 30 minutes for each model change, which seriously affects the flexibility and production capacity of the production line.
Technical principle
WeLinkirt uses multi - view active vision technology to solve the above problems. In terms of algorithms, it uses advanced visual basic models for feature recognition. Through the APDT positive sample/few - sample learning algorithm, it can quickly learn the features of solder joints with only 1 - 20 good samples. In terms of imaging, the self - developed 3D camera can image the hidden solder joints from multiple angles, effectively solving the problem of sparse, noisy and missing 3D point clouds caused by reflective/mirror metal. In terms of hardware principle, through the three - dimensional morphology reconstruction technology, the image information from multiple views is integrated to reconstruct the real three - dimensional morphology of the hidden solder joints, so as to achieve accurate pose recognition and detection. This multi - view active vision technology is effective because it can obtain information about hidden solder joints from different angles, avoiding information loss and interference under a single view and improving the accuracy and reliability of detection.
- Feature recognition of the visual basic model: It can quickly and accurately identify the features of solder joints and improve the detection efficiency.
- APDT positive sample/few - sample learning: It reduces the dependence on a large number of samples and shortens the learning time.
- Self - developed 3D camera: Multi - view imaging solves the reflection problem and obtains more complete point cloud information.
- Three - dimensional morphology reconstruction: Integrating multi - view information to reconstruct the real three - dimensional morphology and achieve accurate detection.
WeLinkirt's solution and products
WeLinkirt provides the DaoAI AI AOI software system and the DaoAI 2D / 3D AI AOI equipment. The DaoAI AI AOI software system has the feature recognition ability of the visual basic model. It can realize 0 - code automatic programming for a good product in 5 minutes. Through APDT positive sample/few - sample learning, it can quickly adapt to different types of solder joint inspections. At the same time, the software system also has the function of semantic false alarm filtering, which effectively reduces the false alarm rate. The DaoAI 2D / 3D AI AOI equipment uses self - developed 3D cameras and three - dimensional morphology reconstruction technology, which can detect hidden solder joints, coplanarity and micron - level morphology. In the implementation method, first, conduct research and analysis on the production line to determine the inspection requirements and parameters. Then use the DaoAI AI AOI software system for programming and learning, and use the DaoAI 2D / 3D AI AOI equipment for actual inspection. Finally, provide feedback and optimization based on the inspection results.
WeLinkirt's solution provides an efficient and accurate means for the inspection of hidden solder joints in the electronics/PCBA industry.
Quantitative results: By adopting WeLinkirt's solution, the detection effect of the manufacturer has been significantly improved. The detection rate has increased from the original 97% to 99.2%, and the missed detection rate has been reduced to <0.8%. The false alarm rate has been reduced by -60%, from 15% to 6%. The model change time has been shortened from 30 minutes to 5 minutes, greatly improving the flexibility and production capacity of the production line.
FAQ
What solutions can DaoAI provide for the detection of hidden solder joints under BGA/QFN packages?
DaoAI provides effective solutions with advanced AI vision technology. It offers the DaoAI AI AOI software system and DaoAI 2D/3D AI AOI equipment, using multi-view active vision technology to improve detection accuracy and efficiency.
What problems exist in the traditional detection of hidden solder joints under BGA/QFN packages?
Traditional detection has many problems. The missed detection rate is 3%, and the false alarm rate is 15%, which increases labor costs and reduces efficiency. Also, the model change time is 30 minutes, affecting production line flexibility and capacity.
What are the advantages of DaoAI's solutions?
DaoAI's solutions have significant advantages. The detection rate reaches 99.2%, the false alarm rate is reduced by 60%, and the model change time is only 5 minutes. The software can achieve zero-code automatic programming, and the equipment can detect various situations.