The Challenge.
- Quality testing is an important part of a manufacturing production line.
- Because quality control is usually done by humans, it can be an important bottleneck in the production process.
- Moreover, only a sample of the produced goods is inspected, and it is assumed that this is representative of the entire batch.
The Solution.
- Designed and built a Machine Learning Computer Vision model to identify quality issues based on images of produced goods.
- Integrated the solution directly into the production line to detect issues in real time.
- Built a dashboard for real-time analysis of quality.
The Results.
- Reduce production costs by reducing time required for quality control.
- Quality control in real-time enables production managers to react more quickly to issues.
- Automated system enables the inspection of every part being produced instead of just a sample, improving the quality overall.