The electronics/PCBA industry has extremely high requirements for product quality and stability. However, the problem of detecting hidden solder joints under BGA/QFN packaging has always restricted the industry's development. WeLinkirt's innovative solution brings new hope to this dilemma.
In the era of rapid technological development, the electronics/PCBA industry serves as an important cornerstone of the technology sector. Its products are widely used in various fields, from consumer electronics such as smartphones and computers to high-end technology areas like automotive electronics and aerospace. In this industry, BGA (Ball Grid Array) and QFN (Quad Flat No - leads Package) are common and important packaging forms. The production line of a leading electronics/PCBA manufacturer involves a large number of production processes for electronic products with BGA/QFN packaging. The manufacturer mainly produces various high-performance circuit boards. The quality of the hidden solder joints under the BGA/QFN packaging on these circuit boards is directly related to the performance and reliability of the entire product. However, due to the special location of these hidden solder joints, traditional inspection methods often have difficulty in effectively detecting them, posing a huge challenge to product quality control.
Pain Points: Why Is It Difficult?
Traditional inspection methods face many quantitative difficulties when dealing with the detection of hidden solder joints under BGA/QFN packaging. In terms of the false-negative rate, since the hidden solder joints are in a complex structure with reflective/mirror-like metals around, the 3D point cloud becomes sparse, noisy, and incomplete. During pose recognition and detection, this incomplete point-cloud information can easily lead to detection failures, resulting in a false-negative rate as high as 3%. This means that for every 100 products produced, there may be 3 products with hidden solder-joint problems that go undetected. These potential defective products flowing into the market can seriously affect the product quality and brand image.
The false-alarm rate is also a major pain point in traditional inspection. In the traditional inspection process, the false-alarm rate reaches 15%. A large number of false alarms not only increase labor costs as manual inspection is required to check each suspected problem, but also reduce production efficiency, disrupting the rhythm of the production line. The main reason for the high false-alarm rate is that traditional inspection algorithms have difficulty accurately distinguishing real defects from false signals caused by factors such as reflection and noise.
The long changeover time is also an important factor restricting production efficiency. Every time a product changeover is carried out, traditional inspection equipment takes 30 minutes to adjust parameters and reprogram. In today's market where demand changes rapidly, the long changeover time seriously affects the flexibility and production capacity of the production line, making it difficult for enterprises to quickly respond to market changes.
Technical Principle
WeLinkirt uses multi-view active vision technology to solve the above problems. In terms of algorithms, it uses an advanced visual foundation model for feature recognition. This model can quickly and accurately identify the features of solder joints, greatly improving the inspection efficiency. At the same time, through the APDT positive-sample/few-sample learning algorithm, it only needs 1-20 good samples to quickly learn the features of solder joints, reducing the dependence on a large number of samples and shortening the learning time. Compared with traditional algorithms that require a large number of samples for training, this few-sample learning algorithm is more efficient and flexible.
In terms of imaging, WeLinkirt's self-developed 3D camera plays a key role. It can image the hidden solder joints from multiple angles, effectively solving the problem of sparse, noisy, and incomplete 3D point clouds caused by reflective/mirror-like metals. Through multi-view imaging, the camera can obtain more complete point-cloud information, avoiding information loss and interference under a single view. In terms of hardware principle, the three-dimensional morphology reconstruction technology is used to integrate the multi-view image information and reconstruct the real three-dimensional morphology of the hidden solder joints. This enables accurate pose recognition and detection, improving the accuracy and reliability of the inspection. Compared with traditional single-view imaging and inspection methods, multi-view active vision technology can capture more comprehensive information of hidden solder joints, thus more accurately judging the quality of solder joints.
Typical Application Scenarios
- Inspection of solder joint cold soldering: Cold soldering is one of the common defects in hidden solder joints. Since the connection between the solder joint and the circuit board is not firm, it will affect the electrical performance of the product. Using WeLinkirt's multi-view imaging and three-dimensional morphology reconstruction technology, the three-dimensional shape of the solder joint can be clearly observed to determine whether there is cold soldering. The difficulty lies in that the manifestation of cold soldering may be very subtle, and traditional inspection methods are prone to false negatives. However, WeLinkirt's technology can improve the inspection accuracy through accurate feature recognition and three-dimensional reconstruction.
- Inspection of solder joint short-circuit: When there is a short-circuit between solder joints, it will cause abnormal product functions or even damage. WeLinkirt's 3D camera can capture images of solder joints from multiple angles. By analyzing the distance and connection between solder joints, it can determine whether there is a short-circuit phenomenon. The difficulty is that the short-circuit may occur in a hidden position, and traditional two-dimensional inspection methods are difficult to detect. However, multi-view imaging can provide more comprehensive information and improve the success rate of short-circuit detection.
- Inspection of solder joint offset: Solder joints may be offset during the soldering process, resulting in a deviation from the designed position and affecting the product performance. WeLinkirt's visual foundation model can quickly identify the features of solder joints and compare them with the standard position to determine whether the solder joints are offset. The difficulty lies in accurately obtaining the pose information of solder joints, and the three-dimensional morphology reconstruction technology can provide more accurate position data, improving the accuracy of offset detection.
- Inspection of solder joint voids: Voids inside the solder joint will affect the strength and conductivity of the solder joint. Through multi-view imaging and three-dimensional morphology reconstruction, WeLinkirt's system can observe the internal structure of the solder joint and detect whether there are voids. The difficulty is that the voids may be hidden inside the solder joint, and traditional inspection methods are difficult to penetrate the solder joint for detection. However, WeLinkirt's technology can discover hidden voids through the integration of multi-view information.
Implementation Case
A large-scale electronics/PCBA manufacturer faced difficulties in detecting hidden solder joints under BGA/QFN packaging in its production line. The manufacturer has multiple production lines and produces a large number of high-performance circuit boards every day. Before introducing WeLinkirt's solution, the false-negative rate of inspection was as high as 3%, the false-alarm rate reached 15%, and each changeover took 30 minutes. During the implementation process, WeLinkirt's team first conducted a comprehensive investigation and analysis of the production line to determine the specific inspection requirements and parameters. Then, they used the DaoAI AI AOI software system for programming and learning, and the DaoAI 2D / 3D AI AOI equipment for actual inspection. During the actual operation, continuous feedback and optimization were carried out based on the inspection results.
By introducing WeLinkirt's solution, the manufacturer has achieved a qualitative leap in inspection accuracy and production efficiency.
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 a powerful feature-recognition ability of the visual foundation model. It can achieve zero-code automatic programming in 5 minutes with just one good sample. Through the APDT positive-sample/few-sample learning algorithm, the software system can quickly adapt to different types of solder-joint inspections. At the same time, the software system also has a semantic false-alarm filtering function, which can effectively filter out false-alarm signals based on the features and context information of solder joints, reducing the false-alarm rate. The DaoAI 2D / 3D AI AOI equipment uses a self-developed 3D camera and three-dimensional morphology reconstruction technology, which can accurately detect hidden solder joints, coplanarity, and micron-level morphology. During the implementation process, first, the production line is investigated and analyzed to determine the inspection requirements and parameters. Then, the software system is used for programming and learning, and the equipment is used for actual inspection. Finally, feedback and optimization are carried out based on the inspection results to ensure the best inspection effect.
Quantitative Results
By adopting WeLinkirt's solution, the manufacturer's inspection results have been significantly improved. The detection rate has increased from the original 97% to 99.2%, and the false-negative rate has been reduced to <0.8%. The false-alarm rate has been reduced by -60%, from 15% to 6%. The changeover time has been shortened from 30 minutes to 5 minutes, greatly improving the flexibility and production capacity of the production line. These quantitative results show that WeLinkirt's solution provides an efficient and accurate method for the detection of hidden solder joints in the electronics/PCBA industry.
FAQ
What solutions can WeLinkirt provide for the detection of hidden solder joints under BGA/QFN packaging?
WeLinkirt provides the DaoAI AI AOI software system and the DaoAI 2D / 3D AI AOI equipment. The software system has the feature-recognition ability of the visual foundation model and the semantic false-alarm filtering function. The equipment uses a self-developed 3D camera and three-dimensional morphology reconstruction technology, which can effectively improve the inspection accuracy and efficiency.
What are the advantages of WeLinkirt's solution compared with traditional inspection methods?
Compared with traditional methods, WeLinkirt's solution has a higher detection rate of up to 99.2%, a lower false-negative rate, a -60% reduction in the false-alarm rate, and the changeover time is shortened from 30 minutes to 5 minutes. It can also learn from few samples and adapt to different solder-joint inspections.
What is the implementation process of WeLinkirt's solution?
First, conduct an investigation and analysis of the production line to determine the inspection requirements and parameters. Then, use the DaoAI AI AOI software system for programming and learning, and the DaoAI 2D / 3D AI AOI equipment for inspection. Finally, provide feedback and optimization based on the inspection results.
This article was generated by AI. Customer cases are simulated scenarios based on real product capabilities and figures are illustrative; see product pages for official benchmarks.