Imperfection recognition on lenses

Challenge

A company manufactures high-quality articles for the cosmetics industry. Specifically, it manufactures a plastic lens to optically enhance a cream container.

Goals:
- Only objects of the highest quality are used: Without scratches, contaminations, inclusions etc.
- Quality inspections should be automated (despite imperfections being difficult for the human eye to detect)
Challenge:
- Process differences of training vs. test data (lighting, background)

Solution

Image recognition by Deep Neural Networks:

Installation of a camera and collection of image data
Labeling images of defective products (manually)
Training a deep neural network
Implementation and integration of the quality assurance into the running production

Benefit

Automation of manual, less “attractive” activities
Increasing the quality of finished products

Your contact

Dragan Sunjka

Lead IT Consultant Automotive & Manufacturing

automotive@msg.group

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