Project Area Description
In this section we present the projects developed by ARAMIS for the Railway industry.
The data collected on fleets of assets are usually very large and difficult to treat for extracting significant insights and information.
This large amount of information contained in big data challenges the asset management, as the number of maintenance strategies to optimize and administrate may become very large.
To address this issue, Aramis has developed a clustering approach for identifying and grouping a subsets of assets with similar reliability behaviors. This enables addressing the maintenance strategy optimization issue once for all the assets belonging to the same group.
The proposed methodology has facilitated the asset management strategy, allowing reducing the number of scheduled maintenance interventions and the associated costs.
Real industrial situations are generally characterized by the lack and the scarcity of field data of normal and abnormal system behaviors. To cope with this, Aramis has developed a fault diagnostic tool based on the First Principle Model (FPM) simulator.
The diagnostic tool is incrementally built from first-attempt, rough solutions based on the limited knowledge, information and data on the monitored system available at the beginning of the development.
Then, the diagnostic tool is incrementally updated and adapted to the evidence of laboratory and field data as these become available, thus improving its accuracy and providing more robust information.
The developed diagnostic tool based on FPM simulator allows overcoming the problems due to the lack of field data, allowing obtaining accurate diagnosis of the degradation state of the valve equipment.
Reviewing of the existing Maintenance program with RCM analysis on different train systems and consequently upgrade of the maintenance time table or modification of maintenance tasks, with the objectives of minimize the maintenance cost preserving the safety standard acceptable for the regulator body