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.
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