Anyone in the transportation industry will tell you how important it is to stay on schedule, because customer satisfaction relies upon it. But with so many moving parts (pun intended) this is easier said than done. Siemens Mobility—a service provider for transport systems with customers that include some of the largest and most vital railways in the world—was looking to maintain customer loyalty by ensuring assets like trains were always up and running.
To accomplish this, Siemens Mobility knew its customers needed a complete, real time view of their assets and their state in order to prevent delays due to equipment failures. The solution to this was an analytics platform that would provide real-time insights into the status of all rail transport systems, which led Siemens Mobility to partner with TIBCO to build their state of the art Railigent platform.
With Railigent, the company allows customers to monitor more than 2,000 components on every single train, in real time, to ensure full functionality and predict maintenance needs before they occur. By using IoT sensors and data analysis at the edge, the platform collects data as a train is traveling; for instance, the vibration patterns of wheel bearings, to understand the condition of each part. If an anomaly is detected, maintenance can be scheduled before a train even arrives at its ultimate destination, in order to decrease downtime.With Railigent, the company allows customers to monitor more than 2,000 components on every single train, in real time, to ensure full functionality and predict maintenance needs before they occur Click To Tweet
“We want to react before something happens, so we can get ahead of the problem. That also helps make the passengers feel safer,” explained Gerhard Kress, VP of data services at Siemens Mobility. “We’re not just telling our customers there is a problem—we tell them exactly what is going on, what actions to take, and we assign a technician group to be there when the train comes in.”
To learn more about how TIBCO helps Siemens Mobility collect and analyze 150,000 data points per second and aided the company in reducing the lifecycle maintenance costs of each train by 30 percent, read the full case study.