2D AI AOI Equipment Achieves Remarkable Results in Detecting Gold Finger Scratches and Oxidation

In the production process of the electronics/PCBA industry, the detection of gold fingers has always been a key link to ensure product quality. WeLinkirt's 2D AI AOI equipment provides an innovative solution to this problem, effectively improving the accuracy of detection and production efficiency.

In the electronics/PCBA industry, gold fingers are the key parts connecting circuit boards to external devices, and their quality directly affects the performance and stability of products. Take the PCBA production line of a leading electronic manufacturing company as an example. After the circuit board assembly process, a comprehensive inspection of the gold fingers on the circuit board is required. Defects such as scratches and oxidation on the surface of gold fingers can seriously affect the signal transmission of the circuit board, leading to product failures. Therefore, the inspection of gold fingers has become a key object of product inspection. With the continuous miniaturization and refinement of electronic devices, the size of gold fingers is getting smaller and smaller, and the surface defects are more difficult to detect, which poses higher requirements for detection technology.

Deep - Dive into Pain Points: Why Is It Difficult?

From a quantitative perspective, traditional detection methods have many problems. First of all, in terms of the miss-detection rate, the miss-detection rate of traditional detection methods is as high as 3%. This means that a considerable number of defective products will flow into the market. Once these defective products have problems during use, it will seriously affect the company's reputation and customer satisfaction. Secondly, the false-alarm rate is prominent, reaching 20%. A large number of false-alarm messages force workers to spend a lot of time on manual re-inspection, which not only increases labor costs but also reduces production efficiency. Finally, the model-changing time is too long. Under the traditional detection method, the model-changing time is as long as 30 minutes. In the face of rapidly changing market demands, such production efficiency obviously cannot meet the development needs of the enterprise.

The root cause of the inability of traditional detection methods to meet the requirements lies in the limitations of technology. Traditional detection mainly relies on manual visual inspection or simple optical detection equipment. Manual inspection is easily affected by factors such as fatigue and inattention, and has limited ability to identify tiny defects. Simple optical detection equipment has a low resolution and cannot clearly capture the tiny details on the surface of gold fingers. It is even more difficult to detect some defects hidden in normal textures. In addition, traditional detection methods lack intelligent analysis algorithms and cannot accurately distinguish real defects from normal surface textures, resulting in a high false-alarm rate.

Technical Principle

WeLinkirt's 2D AI AOI equipment uses high-resolution 2D imaging technology and a deep-learning secondary image-judging algorithm. High - resolution 2D imaging technology is one of the core hardware mechanisms of the equipment. It can capture the tiny details on the surface of gold fingers and accurately convert the appearance of gold fingers into image data. Its resolution can reach the micrometer level. This means that even extremely minor scratches and oxidation defects can be clearly presented, ensuring the complete acquisition of defect information. Compared with traditional low-resolution imaging technology, high-resolution 2D imaging technology can provide richer and more accurate image information, laying a solid foundation for subsequent defect identification.

The deep-learning secondary image-judging algorithm is the intelligent analysis core of the equipment. On the basis of the initial image analysis, the algorithm conducts a second in - depth analysis of the suspected defect areas. Through a large number of positive-sample learning, the model can accurately identify defect characteristics and distinguish real defects from normal surface textures. For example, for some areas with similar shapes and colors to normal textures but actually being defects, the algorithm can accurately determine whether they are defects by learning a large number of positive samples. At the same time, the algorithm also combines semantic false-alarm filtering technology to filter false-alarm information according to the semantic information of defects, such as shape, size, and position. This intelligent filtering mechanism greatly improves the accuracy of detection and avoids a large number of misjudgments in traditional detection methods.

Typical Application Scenarios

• Full inspection of gold fingers after the circuit board assembly process: After the circuit board assembly is completed, a comprehensive inspection of the gold fingers is required. Since gold fingers may be subject to various collisions and frictions during the assembly process, scratches and oxidation defects are likely to occur. The difficulty in detection lies in the fact that there are some normal textures and stains on the gold fingers, and it is necessary to accurately distinguish these normal situations from real defects. WeLinkirt's 2D AI AOI equipment can clearly identify tiny scratches and oxidation defects and accurately filter out normal textures and stains through high-resolution 2D imaging and deep-learning algorithms.
• Inspection of solder joints after the gold-finger soldering process: During the soldering process of gold fingers, problems such as incomplete solder joints and false soldering may occur. These problems will affect the conductivity and stability of gold fingers. The difficulty in detection lies in the fact that the shapes and colors of solder joints vary, and they are similar to the surrounding circuit-board background, so traditional detection methods are prone to miss-detection. The high-resolution imaging technology of this equipment can clearly capture the details of solder joints, and the deep-learning algorithm can accurately identify solder-joint defects by learning a large number of positive samples.
• Inspection of the surface coating of gold fingers: The surface of gold fingers usually has a coating to improve its wear resistance and oxidation resistance. Defects such as uneven coating thickness and air bubbles will affect the performance of gold fingers. The difficulty in detection lies in the fact that the coating defects are usually very subtle and difficult to detect with the naked eye or traditional equipment. The micrometer-level resolution of the 2D AI AOI equipment can accurately detect tiny coating defects and ensure that the coating quality meets the requirements.
• Inspection of the bending degree of gold fingers: During the production process, gold fingers may be bent and deformed, which will affect their connection with external devices. The difficulty in detection lies in the fact that the change in the bending degree is very subtle and requires precise measurement. Through high-resolution imaging and algorithm analysis, the equipment can accurately measure the bending degree of gold fingers and determine whether it is within the qualified range.

Implementation Case

A large-scale electronic manufacturing enterprise has multiple PCBA production lines globally, and its products are widely used in various electronic devices. The enterprise has always been committed to improving product quality and production efficiency, but it has faced many problems in the gold-finger detection link. To solve these problems, the enterprise introduced WeLinkirt's 2D AI AOI equipment. During the implementation process, WeLinkirt's professional technical team provided all-round support to the enterprise, including equipment installation and debugging, software-system programming, and employee training. Through APDT positive-sample/few-sample learning (only 10 good samples are needed), an accurate detection model was quickly established.

After introducing WeLinkirt's 2D AI AOI equipment, the gold-finger detection effect of the enterprise has been significantly improved.

WeLinkirt's Solution and Product

WeLinkirt provides a complete solution centered on the 2D AI AOI equipment. The equipment has the ability of high-speed online full inspection and can conduct a comprehensive inspection of each gold finger without affecting the production rhythm. During the implementation process, the DaoAI AI AOI software system is used for programming, and the 0-code automatic programming of a good product can be completed in only 5 minutes. This efficient programming method greatly shortens the equipment debugging time and improves production efficiency. At the same time, the semantic false-alarm filtering function of the equipment is combined with the software system to further reduce the false-alarm rate. Through positive-sample/few-sample learning, an accurate detection model can be quickly established to ensure the accuracy of detection.

Quantitative results: After using WeLinkirt's 2D AI AOI equipment, the defect detection rate of the enterprise's gold fingers has been increased to 99.2%, and the miss-detection rate has been reduced to <0.8%, effectively preventing defective products from flowing into the market and improving product quality and the enterprise's reputation. At the same time, the false-alarm rate has been reduced by -65%, greatly reducing the workload of manual re-inspection and labor costs. The model-changing time has been shortened to 5 minutes, and the production efficiency has been significantly improved, enabling the enterprise to better adapt to market changes and meet customer needs.

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.