Trenitalia Predictive Maintenance with SAP HANA Case Study

Case studies

WMS

Trenitalia Predictive Maintenance with SAP HANA Case Study

How Trenitalia uses SAP Predictive Maintenance and Service on HANA to shift from scheduled to dynamic, sensor-driven train maintenance.

Published

June 4, 2026

Read time

3 min read

Source

SAP

Trenitalia operates 7,000 trains carrying two million passengers daily. The operator replaced fixed-interval maintenance with real-time condition monitoring using onboard sensors, SAP Predictive Maintenance and Service, and SAP HANA. Data is streamed, stored in SAP IQ, and analyzed to forecast failures, plan interventions, and reduce maintenance costs by 8-10%.

Key takeaways

Shifted from time/distance-based to condition-based maintenance using sensor data

Processes 5,000 signals per train per second through SAP HANA and SAP IQ

Achieved 8-10% reduction in maintenance costs via predictive interventions

Enables advance planning of parts, tools, and resources before failures occur

Manages 700 TB of fleet data annually while cutting in-memory storage needs

Market overview

SCR methodology note

Vendor landscape

Leaders

Implementation considerations

Important consideration

Original Source

Vendors mentioned in this report

No items found.