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Research Group ETA | Energy Technologies and Applications in Production

Main research topic: Energy Optimized Factory Operations

• Deep Reinforcement Learning for operational optimization of industrial energy supply systems
• Interpretability of AI-based operational strategies
• Simulation of industrial energy supply systems
• Analysis of efficiency potentials through digitalization in production
• CO2 reduction by creating transparency in the product development process

KI4ETA | Artifical Intelligence for Energy Technology and Applications in Production

Since the winter semester 2019/2020, Mr. Ranzau is in charge of the topic “Operational Control” in the lecture Machine Learning Applications of Prof. Weigold in the Master's program. This takes place in collaboration with Prof. Metternich, Prof. Klingauf (FSR) and Prof. Kersting (Department of Computer Science). The lecture combines engineering problems with modern methods of machine learning in the context of artificial intelligence. Starting from the mathematical theory of the methods, the methods are explained on the basis of relevant practical examples from the manufacturing industry and critically questioned from the perspective of engineering science. Examples include the use of machine learning for operational optimization, maintenance, in energy management or in quality assurance. In a practical project, students can test their newly acquired knowledge directly on real data from industry.