2D AI AOI Equipment Improves Defect Detection Efficiency in Packaging Box Printing

In the packaging box printing process of the consumer goods industry, industrial vision quality inspection is embracing new development opportunities with the help of advanced algorithms. WeLinkirt's 2D AI AOI equipment provides an effective solution to the problem of printing defect detection with its unique advantages.

User Scenario: A leading consumer goods manufacturer's packaging box printing production line. The main products are various exquisite packaging boxes, and the detection object is the printed content on the packaging boxes. The printing on these boxes includes brand logos, patterns, texts, etc. Various surface defects are prone to occur during the printing process, which have an important impact on the product appearance and brand image.

Pain Points: In traditional packaging box printing inspection, there are many quantitative difficulties. The miss detection rate is relatively high, about 3%, which leads to some defective products flowing into the market and affecting the brand reputation. The false alarm rate also reaches 20%, which causes a large number of qualified products to be misjudged, increasing the re-inspection workload and labor cost. The traditional inspection method relies on manual labor, with high labor cost and low efficiency. In addition, with the frequent product change-over, the change-over time is long, about 30 minutes, which seriously affects the production rhythm. In the new scientific and intelligent system, traditional algorithms are difficult to meet the requirements of efficient detection of complex printing defects.

Technical Principle

WeLinkirt's 2D AI AOI equipment uses high-resolution 2D imaging technology and deep learning secondary image judgment algorithm. High - resolution 2D imaging can clearly capture the tiny details of the printed surface of the packaging box. Its micron-level accuracy can detect subtle defects such as blurred printing and missing characters. The deep learning secondary image judgment algorithm uses a large number of printing defect samples for training, allowing the model to learn the characteristics of different types of defects. During detection, the device first conducts a preliminary analysis of the image, and then uses the deep learning model for secondary image judgment to further confirm the authenticity of the defect. This algorithm is effective because it combines the global features and local details of the image, and can accurately distinguish real defects from normal image interference, thus greatly improving the accuracy and efficiency of detection.

• High - resolution 2D imaging provides a clear image as a basis for subsequent analysis.
• The deep learning model has strong feature recognition ability through learning from a large number of samples.
• The secondary image judgment mechanism reduces misjudgment and improves detection reliability.
• The semantic false alarm filtering function can filter out some false alarm situations according to the semantic information of the defect.

WeLinkirt's Solution and Product

Centered on the 2D AI AOI equipment, this device has the ability of high-speed online full inspection, which can comprehensively inspect the packaging boxes without affecting the production rhythm. Its micron-level detection accuracy can meet the requirements of detecting packaging box printing defects. During the implementation process, combined with the DaoAI AI AOI software system, using the feature recognition ability of its visual basic model, only 1/10 good samples are needed, and 0-code automatic programming can be completed within 5 minutes. At the same time, the semantic false alarm filtering function further reduces the false alarm rate. In addition, the DaoAI World model, as a unified base, provides capabilities such as semantic understanding and cross-scenario generalization, and supports local private deployment without data leaving the factory.

The 2D AI AOI equipment brings an efficient and accurate solution to packaging box printing defect detection with advanced technology.

Quantitative Results: After using WeLinkirt's 2D AI AOI equipment, the detection rate has increased to 99%, and the miss detection rate has decreased to <1%, greatly reducing the risk of defective products flowing into the market. The false alarm rate has been reduced by -75%, effectively reducing the re-inspection workload and labor cost. The change-over time has been shortened to 5 minutes, improving the production flexibility and efficiency.