- Analytics & Modeling - Edge Analytics
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Remote Monitoring & Control Systems
- Sensors - Vibration Sensors
- Agriculture
- Maintenance
- Predictive Maintenance
The process condensate pump, one of the critical pumps in the manufacturing process, has a history of failures every 6 to 12 months. It is a centrifugal pump operating at 3000 rpm with a discharge pressure of 28 MPa (400 psi). Each day this pump is offline, it costs the plant as much as $145,000 in lost production and each failure costs tens of hundreds of dollars to execute an unplanned repair. Nanoprecise Sci Corp was asked to implement a predictive maintenance solution in order to detect faults at an early stage and provide a reliable prediction of Remaining Useful Life (RUL).
We proposed our RotationLF system under which we installed wireless sensors on 7 equipment as a part of a full year contract project.
The specific placement of the RotationLFsensors are selected to monitor:
1)Non-drive side bearing, pump
2)Drive side Bearing, pump
3)Drive side bearing, electric motor
Once installed, strong battery-powered wireless sensors started monitoring pump and motors and sending data to our SaaS-based platform through an encrypted & secured network using Edge and Cloud computing. As data was received, RotationLF platform worked on data analysis using highly sophisticated algorithms.
Approximately one month after the sensors were installed, the system alerted IFFCO that a bearing outer race failure had been detected on the pump. The fault frequency depicted in the system is indicative of an early-stage failure.
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