Trend Moving From Interval-Based to Data-Based Service For Production Machinery
System malfunctions, a possible need for service or available updates are part of everyday life in various areas of our lives. One example is the oil level in a car: In the past, you had to check it yourself with a dipstick, but today the cockpit automatically displays this information – and recommends how many kilometers later the oil should be topped up.
And this is exactly the kind of information that Schuler’s Intelligent Notifications are all about. The only difference is that in the world of presses, it is the responsible maintenance technician who wants to know if, for example, the motor temperature of coupled servo drives deviates by more than five degrees. After all, an early response can prevent unplanned downtimes and reduce wear in the medium term.
The trend is therefore moving from interval-based to data-based service.
The maintenance department is interested in different information than operators, process specialists or the press shop or shift management. In principle, however, the data is analyzed according to the same pattern – for example, by comparing limit values or states under certain conditions. Long-term calculations for recognizing developments are just as much a part of this as the calculation of performance indicators and predictions that show when limits have been exceeded.
Thanks to continuous data analysis, Schuler’s Intelligent Notifications recognize when a deviation occurs and automatically send a message by e-mail. The Stream Analytics Platform calculates the need for action in the current data flow in real time. Users can independently define threshold values and switch notifications on or off. The Settings Module offers setting options for targeted analysis for the various interest groups to which the Message Courier then distributes the notifications. And the Message Hub makes all the collected data available for filtering and editing.
In this way, Intelligent Notifications not only simplify data analysis and reduce the associated workload. They also make it possible to increase efficiency by configuring them according to your own requirements and preferences and to react quickly to critical events. Thanks to the open interfaces, the data can also be further processed with third-party applications.
For more information: www.schulergroup.com