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
Remotely access data from rolling stock
The Railster ensures safe access to real-time data, so that railway operators can perform data analytics and confirm predictive diagnostics in the cloud via rule-based or machine-learning alerts. The Railster is updatable over the air and compatible with major train manufacturers, diesel engine brands and sub-component manufacturers such as doors, HVAC, converters and juridical recorders.
Perform real-time predictive diagnostics
The Railster and Railnova’s rule engine, a software component on the Railster, enable operators to create predictive rules and alerts to detect events and abnormalities in real time. On Railfleet operators can view and analyse those events, and even provide diagnostics tips to the hotline and teams on the ground so breakdowns can be explained and prevented.
Digitalise fleet and maintenance workflow management
The multi-company Railfleet software fills the gap between rolling stock data and maintenance management systems. Operators, maintainers and lessors can efficiently manage their mixed fleets online, turn asset data into predictive alerts and condition-based maintenance orders, and automate ECM day-to-day management.
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.