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Find out about current and future projects.
Digital twins for urban energy analysis
The AI-generated digital twin for brownfield plants
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Complementary machine learning methods for adaptive plant monitoring
CLArA will develop a self-learning condition...
Develop environments for time-sensitive system monitoring and optimization.
In intralogistics, manufacturing companies face...
The use of artificial intelligence can significantly increase the quality and efficiency of product development processes...
In the project "KI4LSA", a solution for traffic flow optimization based on real-time data of existing LSA with...
In the Machine Learning for Production (ML4P) lead project, we assume that the performance in modern production plants...
Machine Learning (ML) for Intelligent...
Development of environments for time-sensitive system monitoring and optimization
The self-learning condition monitoring system is a reliable process monitoring system that enables early and automated detection of errors and problems in the process flow.
The SyDaPro project addresses the generation of synthetic data in production.
Industrial Automation branch INA 