We Stand FOR Collaborative, HOLISTC, and Interdisciplinary Research on System’s LEVEL. RESULTS SHALL be sound, published, and implemented.

The main focus in research is supporting railway infrastructure asset management by data-based (empiric), knowledge-driven, and economically proven procedures. Our algorithms and evaluations support predictive maintenance for track and turnout.

Turnouts

Shifting S&Cs towards data-based predictive maintenance

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Vehicle-Track Interaction

Moving beyond grosstonnes, designing vehicle-based track deterioration models

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Short-waved Effects

On the way towards root-cause based maintenance

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Automatized M&R Planning

Supporting predictive maintenance and renewal planning, achieving network-wide sustainable budgets

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Cost of Non-Availability

Creating a sound cost base for infrastructure maintenance strategies with system’s view

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Maintenance Strategies for increasing Traffic Volumes

Developing new approaches and strategies for highly used railway networks

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