From big data to smart data
Head of R&D: Roman Bobik
Roman Bobik

Smart data and railroad: Railway undertakings have a duty to act

Post from 10. February 2021

Adopting technological progress will be the basic program for utilities in 2021 in order to maintain their competitiveness in the years to come. Companies that want to turn progress into a competitive advantage must proactively address the technologies of tomorrow – now. Modern locomotives have long been equipped with extensive sensor technology that enables operators to retrieve telemetry data anywhere and in real time. This creates an unmanageable amount of data, providing little benefit to the asset operator in its raw form. The task here is to use customized software solutions to link the data from different domains, recognize patterns in it and thus generate smart data. This data can then be used to derive important decision-making aids in the area of maintenance. Read more in the following article.

Digitalization as a fundamental cornerstone for success in railroads

Digitalization and Industry 4.0 are increasingly influencing the rail industry and the mobility sector. Modern rail vehicles, from shunting locomotives and wagons to track-laying machines, are equipped with extensive sensor technology. This enables a wide range of data to be collected and provides real-time information on the condition of rail vehicles. This makes maintenance easier to plan and shortens the time spent in the workshop.

In some cases, failure-based maintenance – and the associated risk – can thus be left behind. In other words, vehicles would only come into the workshop when technical problems unexpectedly arise.


Rail traffic collapses during rush hour

When it comes to rail vehicles, every failure has far-reaching consequences: a commuter train in rush hour on the main line of a metropolis with millions of inhabitants, a loaded freight train on an international freight corridor, or the track-laying machine that has only a narrow window of time for work.
Here, it’s not just individual trains or companies that are affected, but often an entire rail system, because lines are blocked or damaged vehicles forced to travel more slowly.

“To me it is important that we as Boom Software highlight the following: We understand the problems of RUs! So it is also part of our goals as a company to keep failures of railroad assets across Europe as minimal as technically possible. So, we are the experts in breaking down what is technically possible to our customers’ use cases.” – Andreas Schaller


Exploiting the potential of digitalization properly

The digitalization of vehicles and their maintenance has great potential. It enables cost reductions for the train operator (RU) and also for the workshop operator. These savings can not only increase financial returns, but above all ensure competitiveness, and for first movers even a competitive advantage. At the same time, the availability of the vehicles increases, making it possible to plan operations more effectively. Not only does a single company benefit here, but so do all the other RUs that operate on the infrastructures.

In order to fully exploit this potential, it is crucial to correctly understand the overall system, to digitalize it and also to process existing data correctly.


Use data smartly

Sensors or data alone add little value to RU and its customers in passenger or freight transport. The companies often lack in necessary expertise to evaluate the data and to make the best use of the positive effects (cost reduction, higher availability, etc.).

The comprehensive software solution of Boom Software AG can be easily implemented in RUs of all sizes and covers an extensive evaluation of the data with predictive maintenance. Data acquisition, processing and analysis can be easily integrated into existing processes. This makes it possible to detect and predict wear or technical problems at an early stage. In addition, the user has a central decision support tool in the form of the customizable dashboard. This allows users to identify the problem areas of an entire fleet at a glance and immediately plan orders for workshops and other service providers.


A look into the future

But that’s not all. Smart Data enables a look into the future. If the factors influencing the vehicle in operation are correlated with relevant wear data, it is possible to predict how much sooner or later maintenance should be considered in order to ensure maximum availability by determining, among other things, the temperature, load and routing during the planned operation.


Rolling bearings & smart data

There are many influencing factors: Weather, track topology, driving behavior, speeds, weight and much more have an effect on wear. A good example of this are rolling bearings. These fail during operation due to only a few damage mechanisms. It occurs either as a result of insufficient lubrication, characteristic incorrect loads or as a consequence of contamination. The extent of the damage depends in turn on, for example, the respective thermal, tribological or electrical loads and influencing factors. Smart-Data makes experience measurable and thus it is possible to model and calculate the damage kinetics as a function of the load history. This makes it possible to make accurate predictions and look into the future.


A digital twin

So the importance of collecting and processing both sensor data on the vehicle and environmental factors is quite central. Moreover, this data must be understood and linked in order to fully benefit from smart data. As already mentioned, the aim is to provide asset operators with a decision-making aid in order not only to identify threats to vehicle availability at an early stage, but also to be able to derive measures from them.

This is done with the help of the digital twin. This construct makes it possible to define a criticality of the wear indicators after linking wear and environmental data. Thanks to the gigantic computing power made possible by cloud services, among other things, it is possible to calculate precise and, above all, constantly evolving statistical data models. In this recurring process, the criticality of wear indicators can be constantly reclassified and specified.

Software solutions from Boom are a sustainable step towards the future. It is not just about bringing ad hoc solutions, but about providing utilities with tools to evolve with the demands of the market.



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