Textile Defect Detection System
Automatic product inspection is a major concern in the quality control of various industrial products. The textile industry is one of the biggest traditional industries where automated inspection systems play a critical role in reducing inspection time and increasing the production rate.During the process of knitting a textile fabric frame, several types of defects may occur. For instance, the yarn used can be cut then resulting in a gap in the frame, a stain of oil can be caused by the knitting device or a color difference can be marked during the cloth drying. Thus, manual defect detection done by experts becomes quickly an overwhelming and fastidious task.
Therefore, having efficient and automatic inspection systems at hand is a major requirement for improving reliability and speeding up the quality control which may increase productivity.
Our Product For Automated Defect Detection
Our product addresses the textile defect detection problem using an Artificial Intelligence / Machine-Learning and Computer Vision approach.
In textile sectors, different types of faults are available i.e. hole, scratch, stretch, fly yarn, dirty spot, slub, cracked point, color bleeding etc; if not detected properly these faults can affect the production process massively. Our textile defect recognizer product detects all types of faults. This product is a real-time control agent that transforms the captured digital image into an adjusted resultant output and operates the automated machine.
In this system as the product identifies a fault of any type mentioned above, will immediately recognize the type of fault which in return will trigger the laser beams in order to display the upper offset and the lower offset of the faulty portion. This guided triggered area by the laser beams will indicate the faulty portion that needs to be extracted from the roll. After cutting the desired portions of fabric, textile defect recognizer resumes its operation.
Reduce manpower and manual intervention by 90%
Increase the efficiency and accuracy of defect detection by 99%
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Reduce the defect detection time by 90%