Nanoprecise Sci Corp > Case Studies > Detection of a Bearing Outer Race Failure on a critical pump saved downtime cost

Detection of a Bearing Outer Race Failure on a critical pump saved downtime cost

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 Detection of a Bearing Outer Race Failure on a critical pump saved downtime cost - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Edge Analytics
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Remote Monitoring & Control Systems
  • Sensors - Vibration Sensors
Applicable Industries
  • Agriculture
Applicable Functions
  • Maintenance
Use Cases
  • Predictive Maintenance
The Customer
India Farmers Fertiliser Cooperative
About The Customer
India Farmers Fertiliser Cooperative (IFFCO), one of the largest manufacturers of complex fertilizers in India (29% of national production). The Phulpur plant alone produces ammonia and urea with a current throughput of approximately 1.7 million metr
The Challenge

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).

The Solution

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.

Operational Impact
  • [Data Management - Data Availability]

    The RotationLF analytics sensed & detected the anomaly in the pattern and alerted L&T plant staff about this unusual trend automatically through mobile text and email alert

  • [Process Optimization - Predictive Maintenance]

    The RUL prediction of 37 days to failure provided sufficient time to schedule the pump repair during an already planned maintenance outage.

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