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Siemens innovation offers press monitoring at a glance

Product Launches
1 min read

Siemens has developed a solution package for monitoring presses that comprises condition monitoring and predictive maintenance services. In addition to hardware components, Siemens is offering its customers expert evaluations and reports on the condition of the press, enabling optimum predictive maintenance. This concept also makes spare part stocking more effective and provides a transparent overview of press condition. Furthermore, the simple structure and flexible extendibility allow costs to be controlled.

For the modernisation of a production press, a Bavarian automotive manufacturer is now using hardware and software from the newly developed Siemens package. As a result, downtime at the plant has been reduced as possible damage or faults are recognised and remedied early.

The automaker runs a press in which the whole control and drive technology has been replaced as part of a retrofit project. Included in the solution is a Simatic S7 and Simatic IPC 677D with WinCC, while the drive consists of a Sinamics converter and Simotion Motion Control System. The condition monitoring system (CMS) which, among other things, monitors the main drive on the press, has been fitted with the Siemens Siplus CMS4000 system, as well as CMS X-Tools.

Part of the new hardware was located in the control cabinet. Signals from 29 vibration sensors and 24 force sensors are captured by a Siplus CMS4000, and these form the basis of vibration monitoring on the main drivetrain. Vibration signals measured by the CMS here and on other parts of the press are sent to the CMS X-Tools, where they are analysed, visualised and archived.

"The components installed on the press, the CMS and the associated services allow us to provide everything from a single source: hardware, software and our expert knowledge – effectively a turn-key solution," explains Patrick Volkmann, portfolio manager at Siemens.

The approach has three distinct stages. Initially, experts from Siemens and the customer discuss the specific applications, including potential sources of error. Then, sensors, software and hardware are installed, and all the components are connected to the cloud. Finally, experts from Siemens evaluate the captured data and provide the customer with a quarterly report. Siemens is currently working with analytics partner ISPredict to produce algorithms that will support the experts’ work, or even automate it to some degree.

Initial results show that the use of adaptive algorithms (machine learning) is very promising, thus supporting Siemens’ specific goal of providing predictive maintenance for presses.