MRO Analytics and Prediction
Ernsting/DLR
The research area MRO Analytics and Prediction advances the science and application of Prognostics and Health Management (PHM) to enable data-driven maintenance across complex systems. We develop robust methods to transform heterogeneous, high-dimensional data into reliable, context-aware insights for diagnostics and prognostics.
By integrating physics-informed models, statistical learning, and AI techniques, we predict system health, estimate Remaining Useful Life (RUL), and optimize maintenance planning. Our work spans from developing PHM capabilities for components such as engines, batteries and sensors to integrating modules into complete system architectures for aircraft, vehicles, and systems. We focus on deploying PHM systems in operational environments, validating and scaling them for industrial use and serial production.
Through assessment and decision support, we turn data into actionable guidance for maintenance, safety, and operations—bridging the gap between raw sensor data and informed decision-making to enhance reliability, safety, and lifecycle efficiency.
Key Topics
Data Processing
- Feature Engineering
- Data Augmentation
- Uncertainty Analysis/Estimation
Diagnostics
- Anomaly Detection
- Damage Analysis
- System Health Assessment
Prognostics
- Degradation Modelling
- Fault Propagation Modelling
- System-level Prognostics