Case Study: Siemens achieves real-time predictive maintenance and improved train uptime with Equinix

Teradata & Siemens deliver real-time data and predictive maintenance analysis

Siemens Mobility, a leader in rail engineering, built an “Internet of Trains” that collects data from 300+ sensors per train to enable predictive maintenance and higher fleet availability. The company’s challenge was not data collection but storing, managing and analyzing vast, varied IoT data across countries in a cost‑effective, compliant way while keeping analytics performant and secure.

To solve this, Teradata and Equinix delivered an interconnection-first architecture on Platform Equinix with the Teradata Analytics Platform, enabling near‑real‑time analytics, secure cloud and network interconnects, and local data residency. The solution predicts component issues up to three days in advance, improves train uptime, reduces unplanned downtime and costs, scales globally, meets regulatory requirements and enables new uptime‑based service models.

Siemens

Gerhard Kress

Director of Mobility Data Services