Editorial Feature

Using Lubricant Analysis for Predictive Maintenance

Predictive maintenance is essential for machine operation as it assesses the condition of the machine using key health indicators. These are then used to schedule maintenance before it fails.

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One of the main ways to do this is to monitor and analyze lubricant oils for contamination, chemical content and overall viscosity. Lubricants are a critical element in oil wetted machinery. The amount of debris from the erosion of machine parts can cause contamination in the lubricant and therefore, provides crucial insight into the performance and wear of the machine. Analyzing the oil and lubricants on a regular basis allows machine users to schedule maintenance before a failure occurs. This keeps the machine operational, meaning that a plant can have higher productivity, optimal performance and lower cost of ownership.

While the machine is in-service, many types of analysis can be undertaken onsite to provide information about machine wear, lubricant contamination, and condition. The analysis is completed by reliability engineers or maintenance professionals and has long-term benefits for machine operation. In addition to this, the immediate advantages of predicative maintenance are contamination control, condition-based maintenance, and failure analysis.

Most machine owners have an oil analysis program to monitor wear condition, contamination, and degradation simultaneously. Each parameter is tested regularly, and if one parameter changes or exceeds a limit, engineers are alerted, and actions are taken before a problem can occur.

There are different types of contamination which can lead to critical failure of the machine. Solid contamination, most likely sand or dirt is unwanted in oil and lubricant as it adds to the abrasive wear of the machine parts. In addition to this, engine oil can be diluted by fuel and coolant which decreases the viscosity of the lubricant and increases rubbing wear. Both types of contamination must be regularly checked to keep the machine operational.

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Failure analysis is thought to be more costly than traditional predictive maintenance checks, but tests like Ferrography or SEM/EDX can provide the engineer with detailed information about the machine wear. This includes what the wear particles are made of, where they come from, and how severe they are.

While failure analysis tests are thought to be time-consuming and costly, overall predictive maintenance is known to be less expensive than reactive maintenance. Predictive maintenance can help engineers forecast machine performance and schedule repairs as and when needed.

As an example, a large pulp and paper mill in the United States of America was able to use oil analysis to repair a wood chipper before it failed. Had it done, the company would have lost $100,000 in repairs and lost production time. The analysis found that the bearings guiding the chipper shaft were slightly misaligned and were, therefore, causing fragmentation. While it would be impossible to see what was happening with the naked eye, the source was identified, and the machine was repaired before it was too late.

References

  • Efficient Plant. (2007, May 1). Lubricant Analysis Supports Predictive Maintenance. Retrieved from Efficient Plant: https://www.efficientplantmag.com/2007/05/lubricant-analysis-supports-predictive-maintenance/

  • Zhao, Y. (n.d.). The Importance of Lubricant and Fluid Analysis in Predictive Maintenance. Retrieved from Spectro Scientific: https://www.spectrosci.com/resource-center/lubrication-analysis/literature/whitepapers/fluid-analysis-for-predictive-maintenance/

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