The word “machine learning” is used when a machine imitates "cognitive" functions, often associated with humans. Hybrid vision which JLI has introduced is a combination of:
- Machine learning
- Standard machine vision
Hybrid vision is the perfect solution for the classification of defects. Traditional inspection has been done manually as the production
speed is typically fairly low on quartz tube lines.
Replacing manual inspection with standard machine vision solves some of the problems with manual inspection, but for quartz glass tubes, it is mandatory to distinguish between open and closed airlines. This can be achieved by adding Machine Learning to the standard Machine vision system.
The standard machine vision system is able to detect all airlines and other defects. Images of all detected defects are then fed to the machine learning network that returns a likelihood of the defects being one of the typically 4 different types of defect including open- and closed airline.
The machine learning network is trained by pictures recorded earlier from the standard machine vision system, so the cooperation of the two types of vision helps get the system to perform as specified.
This training can be done in a week or so after installation, as the collection of pictures is automated and only a fraction of the pictures need to be sorted manually before training. Sorting open and closed airlines has so far not been possible to do reliably, but with Hybrid Vision, it is now possible.