Case Study | Swiss Federal Railways: Vehicle Identification
Swiss Federal Railways starts digitalisation of relevant processes with RFID vehicle identification
The perfect condition of all rail vehicles not only serves passenger safety, it also prevents potential damage to the infrastructure, such as rail, overhead line or train components. To be able to establish continuous condition monitoring in the first place, the Swiss Federal Railways (SBB) tagged its rail vehicles via RFID. The objective was to identify them in order to locate them exactly and obtain automated data on their condition.
Detecting critical developments early on
SBB Infrastructure is the operator of the train monitoring systems. The objective of the infrastructure operator is to detect defective vehicles at an early stage and to prevent certain events from occurring by taking targeted measures. To ensure that there are no operational disruptions, the infrastructure and all vehicles running on it are permanently monitored. SBB wanted to avoid unexpected repairs to rail vehicles in passenger or freight traffic for safety and cost reasons. In addition, the sudden downtime of trains should be prevented to avoid unplanned repair operations. Proactive maintenance is an important process for a smooth, reliable timetable.
Not digitalised, not transparent
Why SBB opted for reliable vehicle identification with RFID? A solution for real-time transparency was needed. So far, it could be determined that a vehicle was defective, but not which one. Determining the exact vehicle number was not possible. Without reliable vehicle identification, the measurement data on the vehicle condition could also not be transmitted to the responsible vehicle owners. They could thus not benefit from data that provided important information about the condition of components. Correcting noticeable problems early on before they reached a critical level was not possible.
“We see vehicle identification using RFID in Rail as an enabler technology that digitises all processes that rely on vehicle ID."
Stefan Koller, head of train monitoring systems, SBB AG
The domino effect
In the process up to now, it has been possible to identify defective vehicles in time when an intervention threshold was reached, to carry out a service call. However, these unplanned interventions led to disruptions in the transport chain as well as in other traffic and thus had an impact on a variety of different customers – both in cargo and passenger transport. The goal was to prevent this undesired chain reaction in the future.
The beginning: Tagging with RFID
The basis for the desired quality assurance measures was first of all vehicle identification via RFID transponders, which made it possible to allocate the data to a vehicle down to the axle. Only in this way can the vehicle status be reliably tracked via several train monitoring systems and critical developments detected at an early stage.
Monitoring of infrastructure and vehicles
The detection of vehicle axles was ensured via rail contacts installed on the track. By linking this data with the RFID identification data, it was possible to create an intuitive business event that provided information about the condition and individual vehicle data. The result: Real-time transparency of the rail vehicles’ condition. For user-friendly visualisation, KATHREIN Solutions has developed an app tailored to SBB in order to display the determined vehicle data (presence, vehicle number, axles) on mobile devices. This visualisation maps each vehicle with each individual axle and provides an immediate overview or transparency per recorded rail vehicle.
Installed RFID hardware and reading processes
The RFID transponders on the trains as well as the RFID readers installed on the track bed require special robustness that can
withstand any weather. The KATHREIN Reader ARU 3500 is specially designed for harsh environments and is therefore optimally suited for these conditions. The hardware costs could be contained through the internal antenna of the ARU 3500 in a single-track application. In a twotrack application, an additional ARU 3500 is connected as a slave. Through the configured IDs (master and slave) on the main reader, each acquisition can then be assigned to the gelis accordingly. What’s more, KATHREIN equipped all train monitoring systems (approx. 70 locations) with RFID readers and marked the rail vehicles with an RFID tag, according to DIN standard EN17230.
Data acquisition at 180 km/h, snow or heavy rain
The reading requirements of the RFID transponders on the vehicles included vehicle number and track number. In addition, the data acquisition had to be reliable in a range from 5 km/h to 180 km/h. As weather conditions in Switzerland can be extreme, especially in winter, a type of installation was needed that would function perfectly even under challenging weather conditions.
For this purpose, 68 recording points were distributed across the Swiss rail network. 14 are used for single track recording with only one ARU 3500. For the two-track acquisitions, a master-slave process with two ARU 3500 readers was used.
Recording and intelligently processing data
After the RFID readers have recorded the data, it is transferred via the KATHREIN CrossTalk software to the App specifically developed for SBB. Each reading point sends the data to three servers:
- A productive server
- A backup server
- A test server
The RFID hardware is monitored centrally via an internal SBB system, which receives the reader status data via KATHREIN CrossTalk Agent and the CrossTalk Server. KATHREIN CrossTalk also enables the integration of RFID hardware into SBB's leading system. In the process, the KATHREIN RFID reader is made intelligent by means of the CrossTalk Agent, so that they make their status data available to the SBB system.
What started with a pure RFID-based identification for more transparency led to new quality management in the maintenance of the infrastructure. The newly gained transparency provides real-time information about the condition of components, as well as their incipient wear and tear, and warns in good time of any repairs that may occur. Maintenance operations can now be planned in an even more targeted manner without jeopardising timetables. This is a tremendous scoring point for customer satisfaction, both in freight and passenger transport. The digitised information is visualised on a terminal that shows exactly on which rail vehicle a problem has occurred, without having to start a personnel-intensive search for it. SBB made intelligent use of RFID tagging for the digital transformation of key areas. Once the data has been recorded, it can be used in many different ways. Let’s see what journey lies ahead of us in this regard in beautiful Switzerland.
- KATHREIN Reader ARU 3500
- Predictive Maintenance
- Digital early warning system
- Passenger safety
- Investment protection of the infrastructure
- Punctuality of the timetable
- Cost reduction by avoiding unplanned and unnecessarily expensive repair operations
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Case Study (January 2023 | en)