More accurate that human inspectors with Lyophilized Powder
- Challenge: A pharma manufacturer needed to meet regulations for 100% visual inspection of 3-ml glass vials with lyophilized cakes, but manual inspection was challenged by high variability in compliant units.
- 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 90% detection accuracy and a 6% false reject rate, outperforming human inspectors.
