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Wireless Condition Monitoring Predicts Failure Of Calendar Roll Gearbox

 Wireless Condition Monitoring Predicts Failure Of Calendar Roll Gearbox - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Analytics & Modeling - Real Time Analytics
  • Functional Applications - Remote Monitoring & Control Systems
  • Sensors - Acoustic Sensors
  • Sensors - Vibration Sensors
Applicable Industries
  • Equipment & Machinery
Applicable Functions
  • Maintenance
Use Cases
  • Predictive Maintenance
The Challenge

The calendar machine run by a motor has a shaft mounted gearbox connected to the roller. This gearbox allows maximum paper load and feeds the paper with reduced speed to the roller. In spite of scheduled preventive maintenance, it was observed that gearbox used to fail frequently. The rise in vibrations leading to the eventual failure of gearbox adversely affected the quality of the paper. Monitoring the gearbox was thus vital and critical.

About The Customer
A global leading Indian paper manufacturing company specializes in technologically advanced and most eco-friendly paper and paperboards business.
The Solution

Industrial Data Enabler was installed at the bearing location supporting the output shaft of the gearbox to capture tri-axial vibrations and acoustic signals in real-time. After 3 months of deployment, IDE detected a steady rise in the vibrations. A rise in corresponding noise levels was also recorded. Alert notifications were sent via SMS and emails to the registered local as well as remote authorities.

Operational Impact
  • [Efficiency Improvement - Production]

    The remedial measure proved to be successful in meeting the product quality.

  • [Process Optimization - Predictive Maintenance]

    IDE played a significant role in detecting the unexpected failure of the gearbox.

Quantitative Benefit
  • Had the corrective measures not been taken, it would have certainly resulted in calendar roll shaft breakage causing a production downtime to the tune of USD 60 Thousand.

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