Condition Monitoring & Predictive Maintenance

Predictive maintenance, but also preliminary stages such as real-time condition monitoring, increase the availability of your products to customers and enable you to perform better, faster and more efficient maintenance.

Predictive maintenance stands for the predictive maintenance of machines, plants and products:

Based on complex analyses of the collected data, models are developed that predict probable failures. This allows maintenance operations to be planned more efficiently and performance to be stabilized (increasing customer satisfaction).

In most cases, however, it is not only the final stage of a predictive maintenance system that brings great benefits, but also the various stages of condition monitoring: You can keep an eye on the condition of machines and products at all times via dashboards, you can analyze the data that accumulates, recognize patterns or improve processes in service or maintenance via thresholds and alerts.

Exemplary customer projects:

Frauscher Sensor Technology: RMD Project

The "RMD" diagnostic system developed by blue-zone together with Frauscher Sensortechnik collects and analyzes sensor data with the aim of maintaining the performance and reliability of railroad lines.

The company Frauscher Sensortechnik is the market leader in the field of inductive sensor technology for international railroad markets. Tailor-made solutions and the use of Frauscher wheel sensors and axle counters provide rail operators and system integrators with reliable information for safe rail operations.

To further optimize the already available diagnostic system and its data processing, a new higher ranking diagnostic system was developed in cooperation with blue-zone.

With the new system, data from several devices is collected centrally, thus enabling much more detailed queries. The information from the analyses that can be carried out due to the newly gained data depth is optimally prepared and clearly presented for the user on a dashboard as well as detail pages.

This makes it possible not only to analyze the course of sensor data and identify any problem areas, but also to provide early warning of problems that are not yet immediately apparent to the user.

In this way, failures are minimized and Frauscher guarantees its customers the continuous performance and reliability of their operational network.

Client: Frauscher Sensortechnik GmbH

Data logger for data mining and predictive analytics

blue-zone and Track Machines Connected GmbH jointly develop a data logger for recording sensor data from track construction machines.

Together with Track Machines Connected in Hagenberg, blue-zone is developing software to record sensor data on track construction machines and to transmit and further analyze this data in the cloud.

On the data logger, several hundred different sensor values are simultaneously read out, pre-processed and transmitted collectively to the cloud. These sensor values include temperature values, pressure-specific parameters, hydraulic parameters, CAN data, GPS data, and many more.

This enables a more detailed understanding of the machine and its components in order, among other things, to detect any faults that may occur at an early stage and thus to better plan maintenance intervals. The benefit of this is that downtime is reduced and costs are saved as a result.

Main functions

  • Multi-threaded application in C++ with Linux operating system
  • Read sensor data
  • Data pre-processing with appropriate algorithms
  • Secure data transfer to the cloud
  • Data mining and predictive analytics

Client: Track Machines Connected G.m.b.H.

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