Alvaro Zevallos is an acclaimed expert in the railway sector and is passionate about helping railway companies reach their digital transformation business goals.
With the Railnova partner network, Railnova puts itself at the service of technology consulting firms, railway experts and IT departments to accelerate asset digitalisation at railway organisations.
We’ve been working hard on new Railfleet features and updates, to help you optimise your geofencing, diagnostics confirmation and maintenance planning. In this article you can find an overview of the updates that have already been released.
On April 6th the next GPS week number rollover will take place. But, what does this mean for the real-time monitoring of your rolling stock? Railnova has deployed the necessary software updates to properly deal with the rollover, but has your rolling stock supplier done the same?
Der Winter naht, und zum Glück müssen wir uns nicht vor den Weißen Wanderern fürchten. Was wir aber im Auge behalten sollten, sind die bei den kalten und strengen Wetterbedingungen immer häufiger auftretenden Batterieausfälle an Lokomotiven.
Railway operators are now able to better understand the driver’s experience, follow up on the condition of their rolling stock during service, and provide accurate diagnosis and actions from the control room.
Obwohl es sehr verlockend sein mag, den einfachen Weg zu wählen und nur zeitbasiert Wartungen durchzuführen, laufen Sie Gefahr, dass Ihre Fahrzeuge entweder zu oft oder zu selten gewartet werden.
As a railway operator and transit authority, the temptation of predictive maintenance, IoT and AI is often irresistible. However, it's important not to lose sight of what's reality and and what's fiction.
How can edge computing be used in rail: from failure detection to in-service support and usage-based maintenance.
Remote monitoring equipment developed by Railnova is providing a centralised system for fleet diagnostics and is now in use on more than 1000 locomotives and trains across Europe. It is also supporting the shift to predictive train maintenance.