In the semiconductor chip manufacturing process, wire bonding is one of the key processes, and the detection of sunken wires is crucial for ensuring chip quality. DaoAI provides an efficient solution for this detection scenario with its advanced AI vision technology.
User scenario: A leading semiconductor chip manufacturer needs to detect the wires on the chips after the wire bonding process in its chip production. The detection object is sunken wires. Wire bonding is an important step in connecting the chip to the external circuit, and sunken wires may cause unstable electrical performance of the chip, affecting product quality and reliability.
Pain points: The traditional manual detection method is inefficient, with high labor costs and prone to missed detections and false alarms. In actual production, the missed detection rate of manual detection is as high as 3%, and the false alarm rate is about 5%. This not only increases the defective rate of products but also requires a large amount of labor for re - inspection. In addition, when the product is changed, manual detection requires retraining workers, and the change - over time is as long as 30 minutes, seriously affecting the production line rhythm and efficiency. Meanwhile, with the continuous improvement of product quality and compliance requirements in the semiconductor industry, traditional detection methods are difficult to meet the increasingly strict standards.
Technical Principle
DaoAI uses advanced AI algorithms and imaging technologies to solve the problem of sunken wire detection. Its core algorithm is based on the visual basic model of deep learning. By learning a large number of positive samples, it can accurately identify the normal state and sunken defects of wires. In terms of imaging, the DaoAI 2D / 3D AI AOI equipment is equipped with a self - developed 3D camera to achieve three - dimensional topography reconstruction. This imaging method can capture the tiny topographic changes of wires, and can clearly image micron - level sunken defects. The reason is that the deep - learning model has strong feature extraction ability and can learn the feature information of wires from complex images. The three - dimensional topography reconstruction of the 3D camera provides richer depth information for the model, enabling the model to more accurately judge whether there are sunken wires.
- The deep - learning model can master the normal and sunken characteristics of wires by learning a large number of positive samples, improving the accuracy of detection.
- The three - dimensional topography reconstruction technology of the 3D camera provides more depth information for the model, enhancing the model's recognition ability for tiny sunken defects.
- The semantic false - alarm filtering function can effectively eliminate false alarms caused by factors such as image noise and illumination changes, improving the reliability of detection.
DaoAI's Solution and Product Introduction
DaoAI provides a complete solution, mainly involving the DaoAI AI AOI software system and DaoAI 2D / 3D AI AOI equipment. The DaoAI AI AOI software system has the ability of rapid programming. Only 1 - 20 good samples are needed, and 0 - code automatic programming can be completed within 5 minutes, greatly shortening the change - over time. At the same time, the system uses APDT positive - sample/few - sample learning technology and semantic false - alarm filtering function, which can effectively reduce the false - alarm rate while ensuring a high detection rate. The DaoAI 2D / 3D AI AOI equipment relies on the self - developed 3D camera and three - dimensional topography reconstruction technology, which can detect hidden solder joints, coplanarity, and micron - level topography, providing high - precision imaging support for sunken wire detection. In the implementation process, we deeply integrate the software system and the equipment to realize the full - process automation from image acquisition to defect judgment.
DaoAI provides an efficient and accurate solution for the detection of sunken wires in semiconductor chips based on advanced AI technology and equipment.
Quantitative results: By introducing DaoAI's solution, the detection rate of sunken wires of this semiconductor chip manufacturer 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%, greatly reducing the re - inspection workload; the change - over time has been shortened from 30 minutes to 5 minutes, significantly improving the production efficiency of the production line.