Bachelor-/Master thesis: Digital and AI-based failure detection in medical technology

The Institute for Machine Elements and Systems Engineering at RWTH Aachen University conducts interdisciplinary research into a broad spectrum of current and future challenges relevant to both research and industry. The Systems Engineering – Design Methodology division of the MSE focuses in particular on methods of Model-based systems engineering (MBSE) and the application of artificial intelligence (AI) as central elements of future industrial product development processes.

What it´s about:
The early identification of potential failures is essential for developing safe medical devices. However, identifying these failures in current product development is time-consuming and relies on subjective expert judgement. The aim is therefore to apply MBSE and AI methods to achieve more efficient and objective failure identification. To this end, large language models (LLMs) based on MBSE system models should be used to automatically generate failures. Resorbable implants, which degrade within the human body and therefore place particularly high demands on the development process, are being investigated as a use case.

Potential tasks:

• Familiarization with the development of medical devices, with a focus on risk management
• Modelling of failures relevant to resorbable implants
• Automated generation of Failure Mode and Effects Analyses (FMEA)
• Application of AI approaches for deriving failures and generating FMEAs (MBSE system model, knowledge graph)

Prerequisites:

• Ability to work independently and reliably
• An interest in medical technology and digital product development
• Prior knowledge in this field is an advantage, but not essential

What we offer:

• Work on industry-related and research-relevant topics
• Flexibility in choosing your main areas of focus
• Intensive supervision
• Immediate start or by arrangement

We look forward to your application by email:

Philipp Waigand, M. Sc.
Institute for Machine Elements and Systems Engineering

Eilfschornsteinstraße 18, 52062 Aachen
philipp.waigand@imse.rwth-aachen.de