The revolution in automatic defect detection

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Introducing SCIIL VISION: Transforming Manufacturing with Automatic Defect Detection

In this edition, we are excited to introduce SCIIL VISION, an automatic defect detection system based on photographs that is transforming the manufacturing industry. With artificial intelligence and machine learning as its foundation, SCIIL VISION offers an innovative and efficient solution to identify and locate errors such as wrinkles, scratches, and impurities in a very short time.

The Power of Data-Driven Defect Detection

What makes SCIIL VISION so special is its data-driven approach and its ability to learn automatically. Unlike other systems, it learns from data and transfers expert knowledge to artificial models. This enables faster and more efficient training, reducing the time required to implement the system compared to other solutions.
automatic defect detection
Accurate detection is another highlight of SCIIL VISION. Thanks to its ability to analyze different lighting conditions and perspectives, the system can find almost 100% of the defects. This ensures reliable error identification and significantly improves the quality of the final product.
automatic defect detection
But that's not all. SCIIL VISION offers advanced analysis and reporting features, allowing customers to perform remote analysis and obtain statistical information to make informed decisions about the quality of their products. Additionally, the system facilitates automatic rework of detected defects by controlling the corresponding tools for reprocessing. A second image is taken after the initial processing to verify error correction.

In summary, SCIIL VISION is revolutionizing automatic defect detection in manufacturing. Our advanced technology, based on artificial intelligence and machine learning, offers fast and accurate error detection, data analysis, and the possibility of automatic rework.
automatic defect detection
We are proud to help companies improve the quality of their products and optimize their manufacturing processes.
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