This new process significantly outperforms the previous industrial vision system. Profit margins rely heavily on the accuracy of product quality assessment. This process has increased pricing accuracy and eliminated production line outages.
Improving the detection and classification of steel defects.
It’s important to detect and classify product defects to keep the production line up 24/7 and maximize the business value of each coil. Insufficient quality causes a loss of revenue and dissatisfied customers.
Automating the detection and classification of production errors.
We developed a system that combines deep learning based classification with active learning components. Thanks to an expert feedback loop the system will continuously improve itself over time.
The time to predict dramatically decreased while accuracy increased.
We automated the detection and classification of production errors over 50 classes using 50 million infrared camera images per day.