Determine degree of wear of tools
In the HEAD project, Fraunhofer IPT and SCAI are researching how tool wear can be determined automatically from acoustic emission with the help of machine learning. Our goal is to increase both the robustness of the production process and the availability of machines, while maintaining a high production quality.
Here you can play against the AI and determine tool wear visually or audibly - who is better? You can also get assistance from the AI. Frequencies in which new and worn-down cutter heads differ the most are then highlighted (visual mode) or overemphasized (audio mode).
This demonstrator was developed by the department Numerical Data-Driven Prediction of Fraunhofer SCAI. For feedback on the demonstrator or questions related to our offerings, please contact our HEAD team.
- Basic research in the field of information technology, computer technology
- Artificial intelligence, application research (Future Hub)
- Machine learning systems for industrial application, deep learning
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AI for industrial SMEs
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