Data and diagnostics platform
DIANA®Fleet
Up-to-date information on the condition of your rail vehicles for innovative, more efficient handling of your processes
Predictive maintenance
DIANA®Fleet
Data protection-compliant image and video-based condition monitoring to optimize the maintenance and servicing of industrial systems
Predictive maintenance
DIANA®Fleet
Data protection-compliant image and video-based condition monitoring to optimize the maintenance and servicing of industrial systems
Data and diagnostics platform
DIANA.Fleet is an IoT platform that centrally collects and analyzes relevant condition data from rail vehicles and makes it available for further processing. infraView integrates the required sensor systems into the platform, regardless of the manufacturer.
Customer-specific interfaces enable in-depth insights into the quality data of the vehicles in order to identify deviations and trends at an early stage and avoid critical situations and technical failures. The design is modular and geared towards customer-specific use cases and processes.
Through the targeted use of artificial intelligence, manual processes can be successively replaced and used to optimize customer processes.
Who benefits from DIANA®Fleet?
Terminal, ports, industrial plants
Incoming wagons are inspected as part of an incoming wagon inspection in accordance with the AVV catalog. Automated address recognition enables the actual configuration to be compared with the pre-announcement and correction processes can be initiated seamlessly.
Detected damage to the vehicles and load carriers is documented and can invalidate potential claims for compensation. At the same time, potential risks to your infrastructure or internal railroad operations can be minimized.
The recorded condition information supports them in the subsequent train formation process by automating manual activities and avoiding the grouping of defective wagons.
RUs, wagon keepers and hirers
Benefit from condition-based and up-to-date information on the vehicles in use in order to optimize the planning of vehicle deployment and the necessary maintenance. This creates higher vehicle availability at lower maintenance costs and ensures safe rail operations.
Thanks to the availability of high-resolution camera images and damage pattern analyses, wagon hire companies can obtain recurring information about the condition of the vehicle, even after many years of hire. In combination with telematics solutions, comprehensive information can be collected from freight wagons during operation.
Infrastructure operator
Wayside monitoring systems use suitable sensors to record the current status data of passing trains. The data generated is evaluated and analyzed in DIANA.Fleet.
In appropriately designed interfaces, our platform transparently shows when threshold values are exceeded. This means you always have an overview of the status of the rail vehicles deployed on your network.
Appropriate operational measures can be initiated in good time. This leads to a higher level of safety on the railways and protects critical infrastructure such as bridges and tunnels in the long term.
The DIANA®Fleet products
Fleet.Image
Trackside camera systems generate high-resolution images of passing rail vehicles from different perspectives in order to carry out a comprehensive and best possible condition assessment of the asset.
Analysis can be carried out by employees on a PC or with AI support, regardless of location, which increasingly automates diagnostic activities and speeds up subsequent processes in maintenance and SCM.
infraView is currently developing AI modules to map the AVV damage catalog for freight wagons and enables active claim management.
Automated recognition of all addresses on commercial vehicles and load carriers is already available today and replaces time-consuming manual processes.
We attach great importance to a user-oriented presentation and high usability when analyzing the image data.
Fleet.Wheel
Connection of track-side manufacturer systems in DIANA.Fleet for wheelset diagnostics, e.g.
- Hot Box Detectors (HOA) - monitoring axle box temperatures while driving
- Trackside Acoustic Detection Systems (TADS) - detection of acoustic signatures & anomalies with microphones
- WILD systems (Wheel Impact Load Detection) and wheelset diagnostics systems - generation of wheelset measurement values using lasers, ultrasound, optics or similar
Fleet.Wheel processes and displays the condition data transparently. This allows conclusions to be drawn about the predicted wear behavior.
Basis for optimizing the maintenance strategy: The valuable components are monitored and can be extended.
Fleet.Wheel
Connection of track-side manufacturer systems in DIANA.Fleet for wheelset diagnostics, e.g.
- Hot Box Detectors (HOA) - monitoring axle box temperatures while driving
- Trackside Acoustic Detection Systems (TADS) - detection of acoustic signatures & anomalies with microphones
- WILD systems (Wheel Impact Load Detection) and wheelset diagnostics systems - generation of wheelset measurements using lasers, ultrasound, optics or similar.
Fleet.Wheel processes and displays the condition data transparently. This allows conclusions to be drawn about the predicted wear behavior
Basis for optimizing the maintenance strategy: The valuable components are monitored and can be extended.
Fleet.onboard
Continuous and integrated condition monitoring through the integration of vehicle data
Extensive analysis functions for condition monitoring
Causal error pattern detection and performance analysis
Effectiveness analysis of maintenance
Telematics solutions can be integrated to leverage synergies
Cost overview due to malfunctions subject to penalties can be recorded and evaluated using real-time monitoring; detection of severely affected vehicles and derivation of countermeasures
One platform - many perspectives and possibilities
Address recognition
Identification via UIC number, recording of all addresses on load carriers and vehicles, hazardous goods labeling, sequence and position comparison, legal documentation
Optical condition
Recognition of graffiti and covering of addresses, recording of the cleaning status
Damage detection
Detection of damage through image evaluation (manual or semi-automated) on vehicles and load carriers
Automated incoming trolley inspection
Step-by-step development of AI models to cover the AVV catalog (detection, classification, reporting) and integration into DIANA.Fleet
Cooperation with Engineering und Software-Entwicklung GmbH (ESE) for testing & certification of secure software
Data analytics
Quick synchronization between
Target and actual states
Integration modules
Complementary integration of modules such as wheelset diagnostics, onboard functions or existing telematics solutions
Our added value
Automatic error detection
- DIANA.Fleet helps to automatically detect anomalies and errors, supported by rule-based or AI-supported suggestions.
- Automatic alerts are being triggered when limits are exceeded.
Modular solution and standardized interface
- Standardized user interface instead of proprietary GUIs
- New modules can be added easily without causing compatibility problems.
Manufacturer-independent
- All assets in one system - independent of manufacturers, vehicle loggers and condition data suppliers
Complete integration
- Different data acquisition systems and measuring devices can be brought together.
- DIANA.Fleet interacts seamlessly with legacy systems for a unified user experience with high data consistency.
Higher vehicle availability
- DIANA.Fleet generates precise predictions from historical data to determine the future condition of the vehicles.
- Condition monitoring allows inspection and maintenance work to be better planned and resources to be deployed in a more targeted manner.
Take a look at DIANA®Fleet
Want more?
Would you like to find out more? Then download our exclusive product flyer and discover important functions and benefits.
Do you have any questions?
Contact us!
Stefan Schwarz
Head of Rolling Stock
stefan.schwarz@infraview.net
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Sources of the images
1 Adobe Stock
2 Deutsche Bahn AG/ Max Lautenschläger
3 Profile picture/ JK Photo/ Josip Krstanovic
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German