For several years, we conducted a regular (virtual) colloquium with interesting talks around predictive maintenance. The recordings of all of these presentations are listed below.
Dr. Frans Oliehoek – Reinforcement Learning: State of the Art & Challenges
In recent years, we have seen exciting breakthroughs in the field of ‘reinforcement learning’. In this talk, I will give a very basic introduction to this general field, where I…
Dr. Heletje van Staden – The effect of multi-sensor data on condition-based maintenance policies (Nov 3, 2021)
Industry 4.0 promises reductions in maintenance costs through access to digital technologies such as the Internet of Things, cloud computing and data analytics. Many of the promised benefits to maintenance…
Dr. Jeroen Linssen – Applying data-driven techniques to analyse industrial use cases (Sep 1, 2021)
At the research group Ambient Intelligence, we perform applied research: based on real-life use cases we collaborate with external partners to work towards a solution and gain insights from a…
Errol Zalmijn – Applying Causal Analytics for ASML Diagnostics: Results and Challenges (June 30, 2021)
Semiconductor lithography system issues are challenging to diagnose from predefined models and historic data alone. That’s because such systems are characterized by high-dimensionality, non-stationarity and nonlinear behavior across multiple time…
Bart Pollman & Dr. Wieger Tiddens – Smart use of sensor data leads to modern maintenance support in future ships (June 2, 2021)
The Royal Netherlands Navy is planning to introduce several new ship classes within the next decade. The new ships will be technologically much more advanced than the ships currently in…
PDEng Frank Grooteman – Probabilistic analyses and its application to life predictions of aircraft structures (May 12, 2021)
Many aircraft are designed according to the deterministic damage tolerance philosophy to predict the crack growth life of the structure. Alternatively, a probabilistic damage tolerance analysis can be performed, called…