Anhui Keye Intelligent Technology Co., Ltd
AI for Life
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The detection performance is as follows:
| Product model | Number of cameras | scope of test | Detection content and accuracy | Detection accuracy | Detection speed |
| KVIS-MG-CC04 | 4sets | Glove A/B side | Black spots, foreign matter, oil stains ＞ 0.2mm | 99% | Match on-site production speed |
| Hole ≥1mm | 99% | ||||
| Severed fingers, half-shaped forming, missing curling, large tearing | 99% | ||||
| Macular, burnt material ≥0.2mm | 99% |
Inspection principle
In recent years, with the upgrading of customers’ living environment and the development of the housekeeping industry, the demand for household gloves has become higher and higher. The protective effect of gloves on hands is very important. Therefore, the requirements for the surface quality of gloves have become higher and higher. There are more and more complaints about oil stains, black spots, impurities, damage and other defects.
Even if gloves are not directly packaged online, the use of multiple manual inspections still cannot fundamentally solve this problem. Based on the above situation, our company has developed an online visual inspection system for gloves. This breaks through the subjective problem of man-made detection gloves, and realizes online full-automatic detection and removal of gloves. Thereby improving quality, reducing customer complaints, and increasing efficiency.
This system uses 4 high-definition industrial cameras to take pictures of the front and back of the gloves on the two channels of the production line and display them in real time. The system uses deep learning AI technology to automatically learn the characteristics of the glove surface defects, so as to achieve rapid judgment, real-time detection, Real-time removal and other functions. The system has the characteristics of high detection accuracy, missed detection and low false detection rate. The software comes with statistics and defect picture storage functions, real-time monitoring of the operation of the production line, and timely detection of production line problems.
Adopt advanced image visual inspection technology to realize all-round inspection of fingers, palms and cuffs of gloves in motion, identify defective products and realize automatic rejection.
Technical parameter:
Examples of equipment detection defects:
The product passes through the testing equipment and enters the downstream packaging process, which can be completely free of manual labor, avoiding secondary pollution and ensuring the quality of the product.