To ensure that our trains leave the depot on schedule and in optimal condition, it is essential that maintenance machines run efficiently and reliably. If the operating data of maintenance machinery is not collected or not evaluated, maintenance will lack important information about the condition and capacity utilisation of the machinery. Connected, electronic monitoring of this machinery allows you to gain an overall insight and thus optimise the maintenance and servicing processes on a lasting basis.
Optimising the maintenance of maintenance
OT Analytics makes your machine data universally available – regardless of the manufacturer. The solution is immediately fully operational, including uniform interfaces and all components for data transfer, cloud storage and evaluation. The results of this analysis enable you to optimise maintenance and capacity utilisation of your machinery on a lasting basis. All relevant parameters are visible at a glance with the help of a clearly structured dashboard. Furthermore, you can use the data for further analysis or for a digital twin of the machinery.
We offer the following dashboards as a service
Monitoring of an operating area
Diagnosis & final fault
Production resource consumption
Individual customer dashboard
How you benefit
The digitalisation of machine states opens up numerous new possibilities and use cases for maintenance:
- Capture machine data automatically in real-time
- Detect faults at an early stage, remedy them proactively and avoid downtimes
- Optimise the planning of machine usage and maintenance for better capacity utilisation
- Create the ideal data basis for long-term optimisation and digital twins
What is predictive maintenance?
Proactive maintenance or predictive maintenance means continuously collecting machine data in order to draw conclusions about the future behaviour of the machine based on changes in data over time. In this way, the data indicates when the machine is approaching a condition that makes it necessary to take maintenance measures in the foreseeable future. If, for example, vibrations increase in an unnatural way, the software can automatically detect this anomaly and report that a component is in an irregular condition. Sudden failures can then be prevented and maintenance work can be arranged as needed. At the same time, machines do not need to be routinely serviced and taken out of operation if its vital signs still indicate an optimal condition.
OT Analytics in figures
Up to 15 percent reduction in maintenance and servicing costs
Up to 20 percent longer service life for machinery
Up to 10 Percent increase in machinery productivity
4 DB companies already use the service
Would you like to achieve greater efficiency in maintenance and are you looking for a ready-to-use IoT solution specifically for the requirements of Deutsche Bahn? If so, we look forward to hearing from you.