prescriptive maintenance

A Fine-Tuned BERT-Based Model for Individual Log Anomaly Detection in Operational Monitoring at Paranal Observatory

In operational environments such as astronomical observatories, continuous monitoring of system logs is critical yet challenging due to the vast volume of data generated. Manual inspection of these logs is impractical, needing automated methods …

13th International Conference on Mathematical Methods in Reliability

Our team participated in MMR 2025 with three talks showcasing recent advances in data-driven maintenance. The presentations covered applications in the airline industry, distributed systems, and the wine sector, highlighting our interdisciplinary approach to predictive modeling, anomaly detection, and operational optimization.

A RUL Estimation System from Clustered Run-to-Failure Degradation Signals

The prognostics and health management disciplines provide an efficient solution to improve a system’s durability, taking advantage of its lifespan in functionality before a failure appears. Prognostics are performed to estimate the system or …

Improving prescriptive maintenance by incorporating post-prognostic information through chance constraints

Maintenance is one of the critical areas in operations in which a careful balance between preventive costs and the effect of failures is required. Thanks to the increasing data availability, decision-makers can now use models to better estimate, …