Fundamentals of Machine Learning for Technical Plants and Systems

The module provides an introduction to the fundamentals of machine learning in the context of technical plants and systems and illustrates these fundamentals using examples from application systems.
Upon successful completion of the module, students will be able to:

• understand, leverage, and apply the potential of machine learning methods in technical systems and relevant application scenarios,
• select the appropriate method for a given technical problem and perform application-specific adaptations,
• apply the necessary fundamental stochastic and statistical methods,
• apply machine learning methods in the context of state estimation and monitoring, as well as maintenance strategies and predictive maintenance.

Within the scope of the module, the following topics are covered:

• Overview of technical plants and systems in the context of Industry 4.0
• Fundamentals of machine learning in the context of technical systems
• The required basic stochastic and statistical methods
• Model-based, data-driven, and hybrid methods for state estimation and monitoring in technical plants and systems
• The required fundamental methods for the mathematical description of technical systems
• Maintenance strategies and predictive maintenance
• Application of the core learned methods to a digitalized model plant

The lecture-related materials for the course "Fundamentals of Machine Learning for Technical Plants and Systems" will be made available for download on Stud.IP throughout the course of the lecture. These mainly include lecture slides and exercise materials.