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Predictive Maintenance

Decentralized fieldbus system finds faults more quickly

A diagnostic gateway from Murrelektronik allows access to sensor data without additional programming work. This helps it locate the sources of potential faults more quickly.

19 Jul. 2018
HMI-ID07-030kt_MurrElektronik
Decentralized fieldbus system finds faults more quickly (Photo: Murrelektronik GmbH)

Due to their modular design, the Cube fieldbus systems provide expandability for a variety of input, output and mixed modules as well as functional enhancements such as via IO link or an RS-485 interface. Communication data and supply voltage are carried by one system cable, with the device allowing the connection of up to 32 modules at a time to four spurs so that diagnostic data from a wide range of sensors can be collected and analyzed. The new Cube67 diagnostic gateway reads incoming data directly from the Cube system without the need for additional programming, and presents it visually within the framework of a standardized functional program for predictive maintenance that works independently of other software and regardless of what form of control is used.

The fully molded gateway records all process communication and all diagnostic messages. A clear browser-based display is available on any end device with access permissions, whether a tablet or a fixed PC. Individual modules and their associated diagnostic data are shown as a topological representation or in a tabular list, with even isolated error messages being captured in the diagnostic memory and providing information about unexpected fault sources such as a system or machine cable failure that is only occasionally noticeable. Error messages that have been given a name in plain text will automatically receive the same name each time they occur in future and can be paired with a suggested solution. An exchange format allows data to be passed on to ERP or cloud systems. It is not just the manufacturing sector that is currently pushing ahead with the introduction of predictive maintenance solutions, however: electricity supplier E.ON is already connecting it with artificial intelligence to predict malfunctions in its own power grid going forward.