Meet Railnova at the Rise of IoT and Big Data in Rail 2019
The Rise of IoT and Big Data explores both the applications of big data and predictive maintenance opportunities in the Railway industry. We’re excited to be a part of this event again this year, and to present our approach to predictive maintenance by means of a couple of real predictive maintenance use cases.
Don’t miss our presentation on May 28 about Real Use Cases for Predictive Maintenance in Rail at 14h.
Schedule a meeting with us on May 28 or May 29 for a live demo of our remote monitoring and predictive diagnostics products at the event or to learn more about how Railnova is helping operators in their digital transformation and predictive maintenance efforts. We look forward to seeing you there!
- When: May 28-29, 2019
- Where: INFINITY Hotel & Conference Resort Munich, Germany
Railster
The Railster is Railnova’s remote monitoring and edge device. The hardware enables you to safely connect any type of rolling stock or component and stream data to your IT cloud. The platform is easily updated to suit your needs and use cases at any given time.
Railfleet Operational
Railfleet Operational is Railnova’s digital fleet management platform. It allows you to see all your trains in one place, and to communicate about fleet condition, availability and maintenance planning with your stakeholders in real time.
Railfleet Monitoring
Railfleet Monitoring is Railnova’s monitoring and predictive diagnostics platform. It gives you access to train statuses, open alerts and fault codes in real time, which helps you to support your helpdesk and drivers in complex diagnostics situations and to plan the appropriate actions.
Railfleet ECM
Railfleet ECM is Railnova’s platform for ECM scheduling, delegation and traceability. It helps you to report new defects, to manage campaigns and to automatically schedule preventive maintenance based on telematic counters, tolerance and time limits.
Event downloads
Presentation: real predictive maintenance use cases
- How to move towards, and prepare for, predictive maintenance: 5 important steps you should follow in order to successfully deploy predictive maintenance in Rail.
- Examples of real predictive maintenance use cases in rail and our approach to each of these use cases.
Whitepaper: real predictive maintenance use cases
In this whitepaper we’re taking a detailed look at what’s needed to deploy and manage a successful predictive maintenance project in rail.
We’re also sharing a couple of examples of such projects and explain our approach to the use cases that were tackled during these projects.