Case Study: CAF achieves predictive train maintenance and lower lifecycle costs with Spotfire analytics on AWS

CAF extends train component lifecycle by 152% with Spotfire

CAF, a manufacturer and service provider for the railway industry, faced challenges in optimizing train maintenance and operational excellence for its global customers. With increasing market competition and the need to adapt to various deployment conditions, CAF required a highly adaptable analytics platform. The goal was to move from traditional maintenance to a predictive model to reduce lifecycle costs and improve fleet reliability using real-time data. To address this, they turned to the vendor, Spotfire, to build their LeadMind digital platform.

The solution involved building the LeadMind platform natively on AWS, utilizing Spotfire analytics to create over 20 applications for condition-based and predictive maintenance. This Spotfire-powered platform provides interactive dashboards that deliver real-time insights, automate maintenance processes, and securely manage data for multiple customers. The results include a 152% extension in the lifecycle of train components, massive cost savings for clients, and the successful deployment of over 30 projects in 12 countries, including a major contract to monitor trains for Northern in the UK.

CAF