Introduction to Deep Learning for Factory Automation
From the phones in our pockets to the reality of self-driving cars, the consumer economy has started to tap into the power of deep learning’s neural networks.
Deep learning technology is used in advanced manufacturing practices for quality inspection and other judgment-based uses.
Deep learning-based image analysis combines the specificity and flexibility of human inspection with the reliability and speed of a computer.
New deep learning-based software helps machines recognize images, distinguish trends, and make intelligent predictions and decisions.
Deep learning technology is being used to predict patterns and make critical business decisions. This same technology is now migrating into advanced manufacturing practices for quality inspection and other judgment-based uses.
This differs from traditional rule-based machine vision. Traditional machine vision can be better at:
- Gauging & Measurement.
- Precision Alignment.
Manufacturers are turning to deep learning solutions to solve their most sophisticated automation challenges. This can be used in tandem with traditional machine vision. For example, traditional vision may be the best choice to fixture a region of interest precisely, and deep learning to inspect that region. The result of a deep learning-based inspection may then be passed back to traditional vision to take accurate measurements of the defect size and shape.
Benefits of Deep Learning include:
- More consistent results.
- More reliable information.
- Faster processes.
- Easy to configure.
- User friendly interface.
- Designed for hard to solve applications.
We hope that you have found this information useful, we will be posting a follow up blog in the coming weeks on how Deep Learning and the D900 can be used to Decode challenging OCR Applications.
