In the current trend of intelligent manufacturing, the application of AI-AOI technology in electronic product manufacturing has attracted much attention. This technology plays an important role in product quality control and also has great potential in the food industry. WeLinkirt's 2D AI AOI equipment brings an efficient solution for bakery product appearance inspection.
User Scenario: A leading bakery food manufacturer, on its pre-packaging process production line for bakery products, mainly produces various breads, cakes and other bakery foods. The inspection objects are the appearance of bakery products, including the uniformity of surface color, the presence of cracks, the integrity of printed patterns and assembly omissions (such as the absence of decorative parts) and other planar defects.
Pain Points: The traditional manual inspection method has many quantitative dilemmas. The missed detection rate is relatively high, about 3%, which causes some defective products to enter the market and affects the brand image. The false alarm rate also reaches 20%, which leads to a large number of qualified products being misjudged, increasing the re-inspection cost and labor input. At the same time, the manual inspection speed is slow, which is difficult to meet the rhythm requirements of the high-speed production line, and the labor cost is rising year by year. In addition, with the change of market demand, the styles of bakery products are updated frequently, and the change-over time is long, about 30 minutes, which affects production efficiency. In terms of compliance, manual inspection is difficult to ensure the consistency of inspection standards and cannot meet the increasingly strict food safety regulations. Combining with today's hot direction, just as the electronic product manufacturing needs high-precision quality control, the bakery industry also urgently needs advanced detection technology to improve product quality and production efficiency.
Technical Principle
WeLinkirt's 2D AI AOI equipment uses high-resolution 2D imaging technology and deep-learning secondary image-judging algorithm. Its high-resolution 2D imaging hardware can capture the tiny details of the bakery product surface, providing clear and accurate image data for subsequent defect detection. The deep-learning secondary image-judging algorithm is trained based on a large amount of positive sample data. First, the visual basic model is used to recognize the features of the image and identify the possible defect areas. Then, the secondary image-judging is carried out, and the semantic false-alarm filtering technology is used to further analyze the initially judged defects and remove the false alarms caused by factors such as lighting and background. The effectiveness of this algorithm lies in its ability to learn the appearance features and defect patterns of bakery products, and the accuracy and stability of detection will continue to improve with the continuous accumulation of data.
- High - resolution 2D imaging: It can achieve micron-level image acquisition and clearly present the tiny defects on the bakery product surface.
- Deep - learning training: Through APDT positive-sample/few-sample learning (only 1-20 good samples are required), an accurate detection model can be quickly established.
- Semantic false-alarm filtering: According to the semantic information of defects, it can accurately distinguish real defects from false alarms and improve the reliability of detection.
WeLinkirt Solution and Product
Centered on the 2D AI AOI equipment, WeLinkirt provides a complete solution for bakery product appearance inspection. The equipment has the ability of high-speed online full inspection and can comprehensively inspect each bakery product without affecting the production line speed. Its micron-level detection accuracy can ensure the detection of tiny defects, such as hair-thin cracks. In terms of change-over, due to the adoption of the DaoAI AI AOI software system, 0-code automatic programming can be realized in 5 minutes for a good product, greatly shortening the change-over time. At the same time, the semantic false-alarm filtering function effectively reduces the false-alarm rate and the re-inspection workload. The supporting DaoAI World model, as a unified base, can realize semantic understanding, cross-scenario generalization and continuous learning from production-line feedback, further improving the detection effect and the adaptability of the equipment.
The 2D AI AOI equipment brings a high-precision and high-efficiency solution for bakery product appearance inspection.
Quantitative Results: After using WeLinkirt's 2D AI AOI equipment, the detection rate of bakery product appearance defects has increased to 98%, and the missed-detection rate has decreased to < 2%. The false-alarm rate has been significantly reduced by -70%, greatly reducing the re-inspection workload and labor cost. The change-over time has been shortened from the original 30 minutes to 5 minutes, effectively improving production efficiency and adapting to the rapid change of market demand.
FAQ
What kind of bakery product appearance defects can the 2D AI AOI equipment detect?
The equipment can detect planar defects such as the uniformity of surface color, cracks, the integrity of printed patterns and assembly omissions of bakery products. Its micron-level accuracy can detect tiny defects, and the detection rate reaches 98%.
How long does it take to change the equipment model?
By using the DaoAI AI AOI software system, 0-code automatic programming can be realized in 5 minutes for a good product, greatly shortening the change-over time and adapting to the rapid change of market demand.
How does the equipment reduce the false-alarm rate?
Using deep-learning secondary image-judging and semantic false-alarm filtering technology, the initially judged defects are further analyzed to remove the false alarms caused by factors such as lighting. The false-alarm rate can be reduced by -70%.