The big question:
Ukrainian startup produces eco product and wants to reach the capacity of 1,000,000 items daily. It is a challenge, because the quality checking and sorting processes are manual.
Being of natural origin, the items often have variable defects and require additional production cycle to make them ready for use.
- Machine Learning
- Computer Vision
Automated detector of defects
- 5 types of defects inside the item and on its surface are recognized
- Algorithm automatically sorts the items by the identified defect and collects analytics
- 2 supervision points integrated into each assembly line
- User interface shows items with the defects highlighted and general statistics
99% of accuracy in product defect identification. Real-time automated quality check reduces the total production time at the factory.