Improving Reliability of Critical Blower Motors through Predictive Vibration Monitoring

Inside a major fertilizer plant in India, the highly critical Nitric Acid Complex depended on the continuous operation of essential rotating equipment, such as blower motors.

The critical Abator Blower-B Motor in the WNA-6 Unit operates continuously (24×7) at a high speed of 2966 RPM, utilizing SKF 6310 bearings. Maintaining the optimal condition of this asset is crucial to prevent operational disruptions and costly downtime.

The plant team observed anomalies in the operation of this blower while it indicated developing mechanical stress. The plant team noted an anomaly in the blower’s operation, which suggested developing mechanical stress.

Objective

PROBLEM

To ensure uninterrupted operation and maximize the lifespan of critical blower assets, the user sought to implement a system that would provide:

  • Continuous visibility into machine health.
  • Early detection of issues, particularly those related to bearings and excessive vibration.
  • The ability to plan maintenance proactively (predictive maintenance).
  • Prevention of costly unplanned shutdowns.
Solution

SOLUTION

Forbes Marshall implemented the MachPulse – a digital vibration monitoring solution to provide continuous monitoring for the Abator Blower-B Motor.

This wireless solution delivers:

  • Real-time Insights: Continuous velocity trend tracking and real-time vibration trending.
  • Early Fault Detection: Automated diagnostics for early identification of bearing-related anomalies and other faults.
  • Proactive Maintenance: Predictive alerts and actionable recommendations from Forbes Marshall Experts, providing maintenance teams with actionable insights.
  • Scalability: Easy deployment and scalability for critical rotating equipment, overcoming constraints associated with cabling or power.
Benefit

BENEFITS

Zero Unplanned Downtime: Unexpected production stoppages were prevented.

Enhanced Asset Reliability: Significant improvement in equipment uptime and dependability.

Predictive Maintenance Model: Successful transition from reactive, breakdown-based repairs to proactive, data-driven planning.

Operational Confidence: Increased assurance in equipment health through continuous, data-backed monitoring.

Associated Services

Process Optimization

Process Optimization

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Improving Uptime

Improving Uptime

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Forbes Marshal Digital

Forbes Marshal Digital

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Associated Services

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