Keeping an eye on the press condition

With a package of CMS and Predictive Services for Presses, Siemens helps its customers continuously monitor the condition of their presses and avert failures at an early stage.
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Challenge

Making new from old

Even the most reliable press eventually needs an overhaul of its mechanical and electrical components. This was also the case with a press system of a Bavarian car manufacturer in Germany. During a comprehensive retrofit, the electrical components and the condition monitoring system (CMS) were modernized as part of a predictive maintenance approach – with active support from Siemens.

To do this, the press plant was fitted with the control technology of SIMATIC S7 and SIMATIC IPC 677D with WinCC and the drive technology of SINAMICS and SIMOTION. The CMS – which, among other functions, monitors the main drive train of the press – was equipped with the Siemens SIPLUS CMS4000 system and CMS X-Tools.

For Heinz-Joachim Zellmann, Senior Engineer at Siemens who accompanied the project from the beginning, the modernization of the CMS was a logical step: “As the press had to be shut down for the retrofit and we had to replace its individual components anyway, it was a good idea to take the opportunity to upgrade the CMS to state of the art,” says Zellmann. “The CMS ensures there’s no unplanned downtime of the plant, since damage to the drive system can be detected early on, for example.”

With the components installed in the press, the CMS, and the associated services, we ultimately deliver everything from a single source.
Patrick Volkmann, Portfolio Manager at Siemens
Solution

Press solution from a single source

A portion of the hardware installed for the new CMS during the retrofit is located in a control cabinet. Overall, the SIPLUS CMS4000 solution captures signals from 29 vibration and 24 force sensors.

On the hardware side, it serves as the platform for the vibration monitoring of the primary drivetrain. The sensors there and on other parts of the press allow the CMS to capture vibration signals and route them to CMS X-Tools, a powerful diagnostic program. It allows the data to be analyzed, visualized and archived.

In addition, Siemens also offered its Predictive Services for Presses, which included several stations: First, a case is discussed in the consultation between the two cooperation partners, with a focus on possible fault sources. Then, the necessary sensors, hardware and software are installed. And finally, everything is connected to the cloud. Once these steps have been taken, a Siemens expert can evaluate the data and provide a report to the press operator.

Karl Luber, Senior Key Expert at Siemens, is one of the specialists lending his expertise to the project for a final evaluation of the press data. The cloud-based system gives him access to all the data. Luber provides quarterly evaluations that are discussed by the project team. However, the evaluation of this crucial data can’t always be done by individual experts. For this reason, work is underway on training algorithms that can support the expert or, in the future, completely automate the work. This is happening in cooperation with the analytics partner ISPredict, which enables targeted and efficient training of new analytical models.  

Benefits

Detecting damage early on

This new, seamless solution offers several advantages. Patrick Volkmann, Portfolio Manager at Siemens, explains: “Not only can we score points with the fact that we supply the automation and drive technology for presses and are therefore very familiar with it. With the components installed in the press, the CMS, and the associated services, we ultimately deliver everything from a single source: hardware, software, and our expert knowledge. It’s a turnkey solution, so to speak.” Thanks to the quarterly evaluation, measures can be taken at an early point in time if anomalies become apparent.

Once new analytical models are trained, anomalies can be automatically detected in the data and the press operator warned about possible damage. This allows them to plan maintenance well in advance and prevent unplanned downtime. New or altered anomaly patterns can be generated by means of adaptive algorithms (machine learning).

Using Predictive Services for Presses, the cooperation partners found potential for preemptive maintenance with the main drive train and the orientation station of the transfer system. In this section of the press, the position of the component is changed in preparation for the next pressing process. Misalignment can lead to problems ranging from mechanical sluggishness to component damage. Manual evaluation of this data is not possible due to the fast response time required and the complexity of combinations relating to the tools.

Currently, tests are underway to find out how automated analytics of machine data can help operators by using algorithms. The insights obtained so far are valuable for all participants. “We are also able to use the positive findings and experiences in other projects,” says Volkmann. “For example, in plants similar in structure or for other press technologies in which attempts are being made to install similar solutions for the future.”

The complete package delivered by Siemens serves an important goal: preemptive maintenance of the press, whose availability is a prerequisite for productivity. In practice, this means recognizing possible fault sources early on and initiating countermeasures. Standard maintenance intervals, for example, can be used to prevent additional, unplanned downtime.

References

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