The lubricant Optimum Reference State (ORS) is a critical concept in the journey to world-class lubrication and enhanced machine reliability. In short, it is the prescribed state of machine configuration, operating conditions and maintenance activities required to achieve and sustain specific reliability objectives. Lubrication excellence is achieved when the current state of lubrication approaches that of the Optimum Reference State. If you don’t understand the ORS, you probably don’t understand the most fundamental concepts in machine reliability.

Lubrication attributes of the ORS are not widely known by equipment builders, lubricant suppliers and maintenance organizations. Many user organizations falsely conclude that their machines are already fitted with the necessary accessories and components that enable reliability to be achieved. Sadly, of the hundreds of machine service manuals I’ve seen in recent years, it is rare to find practices described close to the ORS. In a typical plant, it is equally rare to see machines fitted with ORS-compliant lubrication components and technicians performing ORS-compliant lubrication.

There are many different attributes of the Optimum Reference State. These attributes relate to people preparedness, machine preparedness, precision lubricants, precision lubrication and oil analysis. Achieving the ORS almost always involves change or modifications. For instance, you can’t get optimum filtration unless you install the optimum filter. You can’t have optimum oil samples unless you install ORS-compliant sample valves in the optimum location. Then, of course, you need to pull the sample using ORS-compliant procedures at ORS-compliant frequencies.

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The most common methods for initial detection of abnormal levels of wear debris in used oils include elemental analysis, ferrous density analysis (DR, etc.), particle counting and patch testing. For some users, because of the criticality of the application, all of these screening tests for wear metals are integrated into the routine test slate.

In such cases, when sampling is done correctly, it would be rare for the abnormal production of wear metals to go undetected. However, when only one or two of these methods are routinely deployed, there is a distinct risk that an incipient (early stage) failure condition may be missed.

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The analysis of power train lubricants for the purpose of detecting faults and abnormal wear patterns is a well developed practiced in mobile equipment applications. However, these same techniques don’t always transfer successfully into stationary equipment applications for many users. In recent years new approaches and techniques have been perfected to substantially improve the detection of incipient and developing faults in bearings and gear units using wear debris analysis. The approach is more systemic as opposed to the application of any singular new or emerging technology. It begins with improvements in the sampling process to enrich the data and proceeds through the use of tactics that strengthen the signal-to-noise ratio. After detection is confirmed, the final analytical phase involves wear particle identification using both classic and advanced techniques. Key Words: wear debris analysis, spectroscopy, wear particles, ferrography, fault detection, predictive maintenance, tribology, wear particle identification, oil analysis, condition monitoring, elemental analysis, ferrous density, microscopic analysis, ferrometrics.

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Too often the viscosity index (VI) is disregarded as a lubricant selection parameter. One reason is simply because it is poorly understood. Some people think the viscosity index is incorporated in the ISO Viscosity Grade, but it is not. It stands alone as an independent lubricant performance differentiator.

We all know that viscosity is the single most important physical property of a lubricant. It is a crude measure of a lubricant’s molecular constitution from the standpoint of hydrocarbon chain size. Viscosity is determined by creating friction between the molecules from fluid movement. The higher the intermolecular friction (longer molecular chains), the higher the viscosity.

Viscosity determines film thickness and film strength in machines. It also influences other important factors such as those in the table below.

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The analysis of power train lubricants for the purpose of detecting faults and abnormal wear patterns is a well developed practice in mobile equipment applications. However, these same techniques don’t always transfer successfully into stationary equipment applications for many users.

In recent years new approaches and techniques have been advanced to substantially improve the detection of incipient and developing faults in bearings and gear units using wear debris analysis. The approach is more systemic as opposed to the application of any singular new or emerging technology.

It begins with improvements in the sampling process to enrich the data and proceeds through the use of specific strategies and tactics. After detection is confirmed, the final analytical phase involves wear particle identification using both classic and advanced techniques.

The post Maximizing Fault Detection in Rotating Equipment Using Wear Debris Analysis appeared first on Tesibis.

The analysis of powertrain lubricants for the purpose of detecting faults and abnormal wear patterns is a useful practice in mobile equipment applications. Unfortunately for many users, these techniques don’t always transfer successfully into stationary equipment applications. In recent years, new approaches and techniques have been advanced to improve the detection of incipient and developing faults in bearings and gear units using wear debris analysis.

As opposed to the application of any singular new or emerging technology, these new methods are more systematic and functional. It begins with improvements in the sampling process to enrich the data and proceeds through the use of specific strategies and tactics. After detection is confirmed, the final analytical phase involves wear particle identification using both classic and advanced techniques.

Like so many endeavors, success depends more on the quality of execution than the strength of the underlying technologies. This idea can be concluded from the fact that while a great deal of new knowledge and technology has been advanced, for the vast majority of industrial organizations employing wear debris analysis, little has changed in either their tools or approach.

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