Bachelor / Master Thesis: Unique opportunity: Building a Decision Support System for the Product Development Process using large-language models and simulation models (de/en)

The Institute of Machine Elements and System Development researches the fundamental structural and tribological behavior of machine elements and depicts this in experimentally validated model descriptions. These model descriptions are used to analyze and design the functional, loss and noise behavior of entire technical systems with a focus on drive technology. The developed models are also used to research and develop methods of model-based systems engineering as a central element of future, inductive product development processes.

This work explores the transformative potential of AI in product development. Based on the existing MBSE model, state-of-the-art AI techniques are implemented to enable seamless access to complex system information and make technical data more intuitive and usable. This work provides an opportunity to redefine the way engineers develop complex systems!

In the KIMBA research project, we are working with leading OEMs, Tier1 suppliers and exciting European companies in AI to develop innovative approaches to the digitalization of product development. The goal is to enable large language modes to interact efficiently with simulation models to accelerate the product development process. I am looking for ambitious students to join this journey!

Tasks:

• Concept and evaluation framework development
• Exploration of different AI architectures
• Design and implementation of a (Multi-) Agent System to assist in product development
• Evaluation of the results
• Written documentation and presentation in the form of a final presentation and a demonstrator
• For more detailed information please contact me

Prerequisite:

• Student in mechanical engineering or similar (Faculty 4)
• Independent, reliable way of working
• Highly motivated
• Good programming skills, preferably in Python
• Nice to have, but not necessary: Experience with AI/ML frameworks (e.g. LangChain etc.)

We offer:

• Flexible organization of work priorities
• Rapid processing options
• Intensive support
• Immediate start or by arrangement
• Very good working atmosphere

We look forward to your application by email:

Vincent Quast, M. Sc. RWTH
Institute for Machine Elements and Systems Engineering

Eilfschornsteinstr. 18, 52062 Aachen
vincent.quast@imse.rwth-aachen.de