When it comes to rolling stock maintenance, our Analytics diagnostic software enables you to leverage unparalleled optimization potential.
Today, the volume of collected and digitally archived data increases exponentially. However, large amounts of valuable data are simply archived and their true potential remains unused.
"Big Data" refers to data records that are too big or complex to manage with traditional data-processing methods. While big data management represents a major challenge, it also harbors enormous process optimization potential.
Our intelligent, self-learning Analytics software module analyzes and utilizes large volumes of recorded data to accelerate and streamline railway maintenance.
The recorded data is used for:
The software uses templates to learn the characteristics of each train type (also see artificial intelligence) and the analysis is performed using pre-defined templates. The diagnostic software uses taught-in templates to automatically check predefined test components for defects or damages. This technology can be used to inspect and analyze different types of trains as well as train components of any kind.
MACHINE LEARNING
The more data is collected, the better the Analytics module "learns" to interpret potential correlations. It intelligently and automatically combines recorded data to generate additional information for every train or component, saving valuable time and ensuring precise rolling stock maintenance planning.
From selecting serviceable components to ordering and stocking required spare parts: The targeted data analysis features enable train operators to minimize lead times, service times and costs.
DETERMINING THE FAILURE PROBABILITY
of single or critical components (predictive)
The Analytics software continuously analyzes newly recorded data, creating a detailed history for each component that can be used to efficiently monitor component wear.
By entering additional information, such as the number of miles or kilometers traveled since the previous analysis, progressive component wear can be predicted and the remaining component lifetime can be forecast in terms of miles or kilometers. Wear parts, such as wearing strips, can be more accurately monitored and replaced in a timely manner to protect against outages at an early stage.
ASSEMBLY INSPECTION AND QUALITY ASSESSMENT OF NEW OR EXISTING COMPONENTS
The Analytics module enables maintenance crews to log, analyze and monitor new components and installation methods.
Sample application: Modifications to the roof structure of every single train can be recorded and individual train profiles can be updated to include newly installed parts, providing a detailed overview of the use of new components within the entire fleet.
This allows for a direct comparison and quality assessments of new and existing components or installation methods. In addition, newly added components can be checked for proper installation and any installed parts that are unsuitable for a particular train model can easily be identified and replaced.
Your advantage:
Our application experts are standing by to answer your calls or written requests. Please call +49 (0) 2630 91590-0 or use the contact form to submit your queries or send an email to support@psi-technics.com
Image Source: PSI Technics, Inodo, AdobeStock
Understand. Challenge the status quo. Consistently move forward: This is our vision of progress. We are advancing digitalization and we are leveraging existing data to create added value for our customers.
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PSI Technics GmbH
An der Steinkaul 6a
56333 Winningen | Germany
PHONE +49 (0) 2630 91590-0
FAX +49 (0) 2630 91590-99
info@psi-technics.com