Master thesis: Method Development for Physics Based Data Driven Remaining Useful Life Predictiona

The Institute for Machine Elements and System Development (MSE) at RWTH Aachen University focuses on research in drive technology, with an emphasis on vibration analysis and condition monitoring of drive train components and systems. Failures in these systems can lead to significant downtime and repair costs, making effective condition monitoring essential. Vibrations-based condition monitoring systems (CMS) are particularly useful, as they allow for early fault detection and enable repairs or replacements during planned maintenance, reducing the risk of consequential damage.
However, current maintenance strategies often face two major challenges: unnecessary downtime caused by overly conservative, preemptive maintenance and in-creased costs or damage from insufficient or delayed interventions. To ad-dress this, condition-based mainte-ance is needed to predict failures as accurately as possible.
This research aims to develop a data-driven algorithm, augmented with the physics of failure mechanisms, to predict the remaining useful life (RUL) of components and optimize maintenance schedules for improved efficiency and reliability.

Tasks:

• Literature review of data driven approaches for remaining useful life (RUL) prediction
• Develop a hybrid framework that integrates physics into datadriven methods to improve RUL prediction accuracy
• Investigate the potential for real-time implementation of the model for predictive maintenance applications.

Prerequisite:

• Interest in machine learning and drive- train technology
• Basics of signal-processing
• Prior experience of coding in Python and MATLAB would be beneficial.
• Independent, reliable and thorough way of working

We offer:

• Future-orientated subject area
• Independent organization and flexible working hours
• Customize work focus as per individual interest

We look forward to your application by email:

Viren Mistry, M. Sc. RWTH
Institute for Machine Elements and Systems Engineering

Eilfschornsteinstr. 18, 52062 Aachen
viren.mistry@imse.rwth-aachen.de