June 14, 2005 When machine on a production line in a factory fails, plant engineers have to react quickly in order to keep production loss to a minimum. Engineers from German ePS & RTS Automation Software GmbH have now developed an Internet-based platform to support service processes at different companies. The ePS Network Service Platform collects and analyzes all relevant machine data to facilitate troubleshooting and shorten response times in the event of a defect. The data stored in the system server can also be used for preventive maintenance in that it identifies machine operation irregularities. Like a flight data recorder, the software registers every movement of a machine or system, creating a comprehensive load profile of the machine on the platform.
All the information is collected and analyzed in a database. If the setpoint values deviate from defined tolerance values, the system will set off an alarm and inform service staff via email or text messaging. Service personnel access the platform and thus the diagnostic data for the machines via an Internet browser.
However, system operators can also authorize direct access to the machine itself. As such, service personnel are able to intervene in the control of the machines and alter key control variables in order to correct faults. Because the platform – and therefore every machine linked to it – can be accessed from any location via the Internet, the system makes it possible to reduce the number of times specialists have to be called in to fix machines, which can be expensive. Passwords and encryption systems protect against access by unauthorized individuals.
In addition, the system continually monitors the condition of the machines by means of test procedures and condition variables and makes this data available on the server in the form of trend analyses. These analyses form the basis for condition-oriented maintenance of the machines. Service personnel are also informed if pre-defined machine operation levels (regarding an axle, for example) are exceeded. All of this helps identify problems before they occur, which in turn reduces machine downtime, thereby boosting productivity.
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