eRDPMS

RDPMS – Remote Diagnostic and Predictive Maintenance System, developed by Efftronics Systems Private Limited for Indian Railways, is an intelligent digital platform designed for Indian Railways to monitor railway assets, identify abnormal conditions, support diagnostics, and enable data-driven predictive maintenance.

RDPMS brings railway equipment health and operational information together through configurable dashboards, forms, alerts, trends, and reports. It provides railway Signal & Telecom and other maintenance personnel with timely information required for monitoring equipment and taking appropriate maintenance action.

DYNAMIC AND CONFIGURABLE RDPMS is built around a powerful dynamic screen configuration framework. Authorized administrators can create and configure dashboards, forms, and operational screens according to the requirements of the railway organization.

The configuration is stored on the server. When the application connects to the RDPMS server, the latest authorized configuration is synchronized automatically and the application dynamically renders the required screens.

This allows new monitoring and maintenance workflows to be introduced through configuration rather than requiring a separate application for every railway requirement.

RAILWAY ASSET HEALTH MONITORING

RDPMS can integrate data from a wide range of railway equipment and systems. Depending on the deployment, users can monitor: • Point Machines • Signals • Track Circuits • Axle Counters • Integrated Power Supply systems • Batteries and chargers • Level Crossing equipment • Equipment-room environmental parameters • Signalling power and field equipment • Other railway assets and sensors

Asset information can be organized by Zone, Division, Station, Location, Asset Type, or other organizational hierarchy.

DIAGNOSTICS AND PREDICTIVE MAINTENANCE

RDPMS goes beyond displaying equipment values. Historical and real-time data can be used to identify abnormal conditions, recurring faults, degradation patterns, and potential equipment failures.

Maintenance personnel can use equipment health information, alarms, trends, events, and diagnostic information to support condition-based and predictive maintenance.

ALERTS AND EVENTS

Discovery signals