In the trend of intelligent manufacturing, the electronics/PCBA industry has increasingly high requirements for detection accuracy and efficiency. DaoAI's 3D AI AOI equipment brings new solutions for BGA void detection with advanced technology.
User Scenario: On the PCBA production line of a leading electronics manufacturer, printed circuit boards for various electronic products are mainly produced. In the BGA (Ball Grid Array) soldering process, the BGA solder joints need to be inspected, and the detection object is the void defects in the BGA solder joints, which is one of the key factors affecting the performance and reliability of the circuit board.
Pain Points: Traditional 2D optical inspection methods have many difficulties in detecting BGA voids. The miss-detection rate is relatively high, about 3%, which causes some defective products to flow into subsequent processes, increasing the product rework rate and cost. The false alarm rate also reaches 20%. A large number of false alarm messages require manual re-inspection, wasting a lot of manpower and time. In addition, when changing the product model, the programming and debugging time of traditional inspection equipment is long, about 30 minutes, which seriously affects the production efficiency. In the intelligent manufacturing scenario, the demand for optimizing the actual effect of AI-AOI industrial vision inspection using fine-grained labels is becoming increasingly urgent, and traditional methods can no longer meet the requirements of industry development.
Technical Principle
DaoAI's 3D AI AOI equipment uses a self-developed 3D camera for imaging. Its principle is based on the structured light three-dimensional measurement technology. By projecting a specific structured light pattern onto the surface of the detection object and then using the camera to capture the deformation of the reflected light, the three-dimensional coordinates of each point on the object surface are calculated according to the triangulation principle, thus realizing three-dimensional shape reconstruction and generating point cloud data.
- For BGA void detection, the equipment can detect defects in 2D optical blind areas such as hidden solder joints, coplanarity, micron-level morphology, and air holes. This is because 3D data can provide more abundant information. Compared with 2D images, it can observe solder joints from multiple angles and accurately judge the existence and size of voids.
- At the same time, the equipment uses 2D-3D fusion technology, which combines the texture information of 2D images and the geometric information of 3D point clouds to further improve the detection accuracy. By learning and analyzing fine-grained labels, the equipment can more accurately identify different types of defects, thereby optimizing the detection effect.
- At the algorithm level, the equipment uses deep learning algorithms to train a large amount of sample data, continuously optimizing the model's feature recognition ability, enabling it to quickly and accurately identify defects such as BGA voids.
DaoAI Solution and Product
Centered on the 3D AI AOI equipment, DaoAI provides a complete inspection solution for the electronics manufacturer. The equipment has high-precision detection capabilities and can accurately detect BGA voids. Its self-developed 3D camera and three-dimensional shape reconstruction technology can effectively overcome the limitations of 2D optical inspection and detect hidden defects.
The 3D AI AOI equipment combined with fine-grained label learning brings new breakthroughs to BGA void detection in the electronics industry.
In the implementation process, the DaoAI AI AOI software system is used as a supporting tool. This system supports 0-code automatic programming for a good product in 5 minutes. Through APDT positive sample/few-shot learning (only 1-20 good products are needed), it can quickly adapt to the detection requirements of different products, greatly shortening the model change time. At the same time, the semantic false alarm filtering function of the system can effectively reduce the false alarm rate.
Quantitative Results: After using DaoAI's 3D AI AOI equipment, the detection rate of BGA voids of the electronics manufacturer has increased to 99.2%, and the miss-detection rate has decreased to <0.8%. The false alarm rate has been reduced by -65%, greatly reducing the workload of manual re-inspection. The product model change time has been shortened from the original 30 minutes to 5 minutes, and the production efficiency has been significantly improved.
FAQ
Can the 3D AI AOI equipment detect other types of BGA defects?
Yes. The equipment can not only detect BGA voids but also defects in 2D optical blind areas such as hidden solder joints, coplanarity, and micron-level morphology. The 2D-3D fusion technology improves the comprehensiveness and accuracy of detection.
Does using the DaoAI AI AOI software system require high technical skills from operators?
No. The system supports 0-code automatic programming for a good product in 5 minutes. APDT positive sample/few-shot learning only requires 1-20 good products, which reduces the technical threshold for operators and can quickly adapt to different product inspections.
What benefits can the reduction of product model change time bring?
Shortening the product model change time from 30 minutes to 5 minutes can significantly improve production efficiency, reduce equipment downtime, make the production line more flexible in meeting the production needs of different products, and reduce production costs.