More accurate than human inspectors for molded glass
- Challenge: A CMO recently failed numerous AQLs from semi-automated visual inspection and was looking for a solution to inspect their powder-filled molded glass container.
- Solution: Our compact automated system uses unsupervised machine learning to create an inspection recipe from the normal variation in 500 pre-inspected vials.
- Outcome: A feasibility study showed over 98% accuracy and a 3% false reject rate for defined defects, far surpassing human inspectors.
