Spain-based CAF is a leading designer and manufacturer of trains and railway-signaling systems. The Rail Services unit reduces maintenance costs over the lifecycle of a train using predictive maintenance, a process that schedules repairs by interpreting real-time operational data.
CAF launched a new initiative called Digital Train, which led to the development of the LeadMind platform. LeadMind utilizes Internet of Things (IoT) technology to deliver predictive maintenance using data captured by sensors on trains in real-time.
Javier de la Cruz, rail services engineering head manager at CAF-LeadMind, says, “We run our entire IoT infrastructure in the AWS Cloud because of AWS's broad range of services in analytics and machine learning, as well as the pay-as-you-go pricing model and easy implementation.”
The LeadMind Platform securely connects its train-based sensors using AWS IoT Core. The platform currently collects 15 GB of train performance data from 30 trains every day. “With the elasticity of AWS IoT Core, we can easily scale LeadMind’s capacity up to hundreds of trains,” says De la Cruz.
Amazon Kinesis then ingests the IoT data in real time and sends it to Amazon Redshift, which acts as a data warehouse while also integrating with CAF’s business intelligence tool for data analysis. The analyzed data highlights the performance of train components—from the operation of the air conditioning units to the effectiveness of the braking systems.
“Because of the managed services in AWS, LeadMind and our data scientists have additional time to create more-effective predictive maintenance models to help customers quickly identify potential issues with trains and maximize standards of safety,” says De la Cruz.
To learn more, visit aws.amazon.com/iot-core.