Třinecké železárny uses a SINAMICS S120 drive with two motor modules to drive two motors on the Sizing Milldevice. The customer considers these motor modules as critical, hence the requirement of minimizing the downtime and increase the availability. The evaluation of the criticality has been performed considering the cost of a shutdown caused by a failure of this drive.

The Siemens Predictive Service Analyzer (PSA) application was installed to monitor and provide predictive maintenance on these drives. PSA works with low-frequency and high-frequency data from the monitored control unit (Siemens SINAMICS CU 320-2 PN) for both the motor modules of the selected device. To ensure the collection of high-frequency data, the TRC Data technical library was installed in the main control unit to be able to collect the necessary parameters and forward them to the given industrial Edge Device (SIMATIC IPC427E) where the PSA application is running.   

Evaluation of the project: 
During the pilot project, the PSA application was successfully installed and put into operation to collect data from the selected motor inverters. Over a period of six months, data was actively collected and continuously evaluated by the PSA application. The activated PSA application modules functioned correctly, and the evaluated results corresponded to real-world conditions. 

Here are the key findings from the individual PSA application modules: 
1. AI for converter 

• A few hours of overload mode were detected during the entire monitored period of approximately six months. 
• Most operating hours were measured in the load range from 0 - 33%.
• There was no significant and frequent overheating of the switching elements of the frequency converter.

2.  AI for applicaton  

• The real-time operation of the device was compared with the selected reference period, with which this module was trained. 
• The module correctly evaluated various situations when individual monitored parameters deviated from the learned values, reporting warnings or alarms in those cases, thus enabling the maintenance personnel to timely act and minimizing the risk of an unplanned shutdown. 
• The module would display more accurate results if retrained based on a larger amount of raw operational data.

3.  Virtual temperature sensor 

• This module provided a calculated temperature values on the motor engine components. The measured values never exceeded 50°C.

Conclusion: The pilot installation of the PSA application demonstrated the functionality of its individual modules and their purpose. The application confirmed the correctness of the monitored devices settings and identified situations when the device operation deviated from normal. The PSA application allows for the prediction of potential future failures on the monitored device. However, during the pilot period, the absence of an Internet connection and remote access to the device made it challenging to actively respond and monitor the outputs from the PSA application. Additionally, it was not possible to update the PSA application to a higher version released during the pilot project. Overall, the PSA application from Siemens successfully detected alarming states on the monitored technological equipment, alerting to situations above the limit. These unwanted states can be threatening to the equipment and lead to irreversible changes. Thanks to the artificial intelligence integrated into the PSA application modules, it is possible to predict future states and prevent situations that could be threatening to the production.