A steel plate manufacturer was in need of an automated inspection solution to minimise human intervention, thus saving costs, time and labour.
This case study discusses how Nitor Infotech’s Cognitive Engineering expertise in Deep Learning-based computer vision predicted product faults with 80% accuracy automating a time-consuming standardized task.
Case study Highlights:
Their challenge: Rising demand to automate the finished goods quality inspection
Our Solution: Design and execute a Deep Learning model
The Impact: 80% accuracy in predicting steel plate faults
Download our case study now to read more about:
- Business need
- Solution
- Business value
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