Machine learning: a new benchmark in quality assurance
ML-S-LeAF stands for an innovative approach to quality assurance in additive manufacturing. The project, which is funded by the German Federal Ministry for Economic Affairs and Climate Protection, aims to make manufacturing processes more resource-efficient.
The aim of the research consortium is to develop an automated process monitoring system based on simulated noise emissions during an industrial printing and melting process.
Our contribution to ML-S-LeAF
As a partner in the ML-S-LeAF project, we are responsible for the generation of virtual sound data through simulation. Our focus is on the transition from a traditional physics-based analysis to a data-driven methodology. We use innovative methods such as polynomial chaos and decision trees to realistically simulate the complex variables and events of process monitoring.
Follow our progress
We continuously share the ongoing developments and successes of ML-S-LeAF on LinkedIn. Follow us to get the latest updates and learn how machine learning is revolutionizing the manufacturing industry.
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