6 months have been enough to obtain tangible results with LeadMind, CAF´s digital platform, in the maintenance of the fleet TMB (Transportes Metropolitanos de Barcelona) of line 5, specifically the S/5000.
The goal of the project is clear, improve the maintenance strategy to reduce the maintenance cost and ensure the availability and safety of passengers on board the Barcelona metro. On the way to achieve this objective, over the course of these months LeadMind is facilitating the monitoring of the health status of the fleet and applying the ISO 17359 condition-based maintenance methodology.
The project began in late August 2020 with a Data Lake taken from 8 UTs. The Barcelona fleet maintenance team selected the most critical assets such as air conditioning, doors and air generation to analyze their behavior in LeadMind and thus see the results in predictive maintenance.
During these months of activity, different indicators have been proposed, evaluated and validated to detect anomalies and predict breakdowns that may cause an incidence in the service. Anomalies in the operation of doors, compressors and air conditioning have been detected with great accuracy thanks to LeadMind algorithms based on knowledge and experience in the manufacture and maintenance of railway fleets.
This information has allowed, on several occasions, a predictive intervention to the first symptoms. Thus, the foundation is laid for condition-based maintenance that avoids the over-maintenance caused by mileage-based planning and that allows to capture savings in interventions.