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Cognex Vision Helps Shorten the Defect Detection Time and Ensures Quality Control

Cognex Vision Helps Shorten the Defect Detection Time and Ensures Quality Control

Bios Time Inc., founded in 1999 and based in the Guangzhou province of China, is a company that manufactures a variety of maternal and child nutrition products, including probiotic powdered drinks, baby and infant powdered milk, mother’s milk powder, and many of other nutrition and health products. Bios Time cooperates with several international strategic partners, including Lallemand Group, laiterie de Montaigu, Diana Naturals from France, and Kerry Company from the US to do research and development work in the high-tech dairy products industry.  The company operates a class 100,000 GMP plant that manufactures probiotics and food products that is recognized as one of the best clean room probiotics plants in China.  In addition, Bios Time has set up 11 sales regions and 52 offices across China.

In order to adhere to the Bios Time corporate concept, “to make excellent products, quality becomes our responsibility”, the company required a more sophisticated approach to detecting defects and ensuring product quality control. The goal on the production line is to ensure that every product packaged in a box have the exact same serial number printed by the laser printer. Prior to deploying a Cognex machine vision system, when bar code errors or printing errors occurred and were detected the production line had to be stopped so that a correction could be made manually in the barcoding process. This approach was inefficient and could not guarantee the quality of product packaging because the naked eye can become tired and as a result, substandard product may pass through the production line.

In order to address these quality control challenges, Bios Time decided to adopt an approach in which product data is collected and uploaded after the machine vision system completes its inspection. Using this approach guaranteed the packaging quality, improved the level of automation, and increased overall productivity.

After testing several machine vision systems, Bios Time decided on the Cognex system because of overall performance stability and because the accuracy rate in reading OCR with the In-Sight® Micro vision systems and the accuracy rate in reading bar codes by the DataMan® 100Q fixed-mount reader satisfied their requirements.

The In-Sight Micro was installed directly in Bios Time’s production lines. The hardware included In-Sight Micro 1403 smart cameras to read the OCR, DataMan 100Q barcode readers, light sources, and pick-up devices.  The system also included control and management software for the entire defect detection process.

The machine vision hardware and software systems work together to provide real-time monitoring and statistics collection on Bios Time’s production line. After the security label is affixed to an object by the labeling machine and the serial number is printed by the laser coding system, Cognex’s online recognition and control system directs the code readers to read the bar codes on the security labels. At the same time, the In-Sight Micro 1403 vision systems read the serial number on the product box, compare the data read by the cameras and those printed by the laser coding system, and automatically reject the products with recognition errors found by the smart cameras.  These errors include things like repeated serial numbers and products without security codes. Then, the vision systems direct the coding printer to print bar codes for medium and large size boxes according to planned packaging proportion for later manual packaging and shipment.

Overall, the Cognex products have provided Bios Time with a highly stable and accurate way to eliminate defective products.  Both the In-Sight Micro and DataMan 100Q systems are compact, easy to integrate, and feature powerful and flexible software functionality. The system has been adept at verifying and improving product packaging quality, productivity, capacity, and the degree of production automation.

 




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