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Modern vehicles are equipped with sensors that continuously monitor the health of components. The availability of sensor measurements opens up the opportunity to analyse degradation trends over time, and to plan maintenance accordingly. We aim to develop predictive maintenance models for fleets of vehicles whose health is continuously monitored by sensors.
In this research project you will analyse datasets and investigate the degradation trends of components based on time series of measurements. You will be working towards accurately estimating the degradation of components and striving to predict when failures are likely to arise. For this, you will develop Remaining-Useful-Life (RUL) prognostics using machine learning algorithms and/or stochastic processes.
You will further develop optimisation models that integrate RUL prognostics to schedule maintenance tasks (e.g., component replacement, component inspection). The objectives of the optimisation models are: to minimize maintenance costs, maximize the lifetime of components, and limit the probability of a failure. You will use RUL prognostics to guide the scheduling of maintenance tasks.
By conducting simulations, you will analyse the performance of your RUL prognostics and optimisation models.
This is a PhD position for 5 years, which includes research as well as teaching. You will spent approximately 30% of your time on varying teaching support activities. We offer the opportunity to take significant steps towards acquiring a basic teaching qualification (BKO), which qualifies you as a teacher in the Dutch higher education system.
We are looking for an enthusiastic new colleague who meets the following criteria:
In addition to the employment conditions from the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. These include agreements on professional development, leave arrangements and sports. We also give you the opportunity to expand your terms of employment through the Employment Conditions Selection Model. This is how we encourage you to grow.
For more information, please visit working at Utrecht University.
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