– An innovative tool for predictive maintenance –

CAF LeadMind is a multi-platform solution resulting from a close collaboration among different departments and business units in the CAF group. It provides an open, customizable and client-oriented solution that respond to the needs of the different agents involved in the railway chain. Four well-differentiated technological areas (connected digital train, big data, cibersecurity and analytics) are interconnected to create a unique ecosystem that collect and analyze data from our trains with a simple objective, to reduce the life-cycle-cost and to increase competitiveness.

Condition Based Maintenance (CBM) is one of LeadMind’s core competences, favouring optimal decision-making through health condition monitoring of machinery in real time. Current capabilities of collecting sensor and real condition data from our machines allows LeadMind to focus attention in the subset of assets needing real intervention, hence being able of reducing unnecessary maintenance operations and improving reliability.

Advanced analytics is used for Prognosis and Health Management (PHM) within the CBM program, with the aims at predicting the Remaining Useful Life (RUL) of the different components using historical records (telemetry and maintenance activities) and degradation trends observed from condition monitoring data.

Use cases, such as the use of CBM indicators for predicting failures in batteries and compressors in Euskotren with 85% accuracy, support our confidence in a continuous improvement. PHM uses stored data to build health/CBM indicators, define control limits or failure thresholds, and finally predict the RUL of the assets.