A global sustainable resources group uses Aicadium’s computer vision defect detection for paper manufacturing quality control
Need
A global sustainable resources group wanted to detect stack defects in paper reams and develop a scalable solution to be deployed across their production plants.
Solution
The group uses Aicadium’s computer vision modeling for classification, trained on photos of quality control defects and historical pass/fail records. The solution was able to learn from individual production lines and then scale across multiple plants.
Impact
The model achieves a higher level of defect detection accuracy than ever before. With the fast, accurate deployment of a new line within weeks rather than months, the solution has a fast time to impact for the business.