Intelligent Systems and Machine Learning for Production Processes

Lecturer: Prof. Vogel-Heuser
SWS: 2+1
Exam: written/ oral (90 min, German)


The goal of the module ISMLP is to convey a structured development methodology for intelligent mechatronic systems. In addition to the special features of technical systems and their development, this course teaches methods from research and industry that enable students to develop structured approaches. For this purpose, different description tools are taught, which can be used to model mechatronic systems. This includes the Systems Modeling Language (SysML), which is established in Model-Based Systems Engineering, as well as, for example, the Object Constraint Language (OCL), which is widely used in computer science and enables an automated testing of the models created. The modeling is supplemented by the aspect of intelligence of such technical systems. For this purpose, concepts of agent-based systems are taught, which enable self-organisation of mechatronic systems and thus increase their flexibility and adaptability. In addition, Semantic Web Technologies as a technology for knowledge representation as well as approaches of data analysis and machine learning in the context of mechatronic systems are central parts of the lecture. The lecture "Intelligent Systems and Machine Learning for Production Processes" complements and replaces the lecture "Entwicklung intelligenter verteilter eingebetteter Systeme in der Mechatronik".

Schedule for Lecture and Excercise

see TUMOnline



Bernhard Rupprecht, M.Sc.