Tracking the Life Cycle of Your Lubricants

Noria Corporation

What do you do with your oil analysis data? Do you thumb through the results looking for outliers and act upon those? Do you look at histories and gauge expectations against current analysis? There are many ways to set up and run an oil analysis program. In this article, I’d like to suggest another way of utilizing the data to help achieve your reliability and lubrication goals.

The evolution of an oil analysis program is easy to understand. The first iteration consists of taking a sample, sending it off to the lab and receiving results. These results are looked at on a case-by-case basis and are acted upon. In this scenario, even if the “rights of oil analysis” are followed perfectly, there is still a lot of value being left on the table. The rights of oil analysis include the following:

The Right Lab

Some organizations use an in-house laboratory for basic tests like viscosity, particle counts and moisture content but utilize an outside lab for exception testing. Knowing the quality of your outside lab is extremely important. Even though the reports from many labs look similar, the data and results contained within these reports can be very different.

The Right Test Slate

Frequently, companies enter into a relationship with a laboratory without really knowing what they want. They rely on the lab to steer them in the right direction regarding the tests to run. In some cases, the “standard” test slate may not capture the information needed to make the best maintenance decisions. Therefore, it is imperative to work with your laboratory to determine your individual needs and develop the proper test slate.

The Right Sampling Location

It is critical that samples are taken from the proper location within a system that maximizes data density and minimizes data disturbance.

The Right Frequency

Several factors should be considered when determining the sampling frequency, such as the age of the equipment, the age of the lubricant, the machine’s criticality, etc.

The Right Procedure

You must ensure that each sample is representative of the fluid in the reservoir and not affected by outside contaminants. The right procedure must be documented so no matter who takes the sample, it comes from the same place in the same way every time. This is what makes the results repeatable and allows for data trending.

The Right Equipment

Sampling equipment should be kept in a clean environment and cleaned after each use and prior to storage.

The Right Alarms and Limits

The primary purpose for alarms or limits is to filter data so that the technologist spends his or her time managing and correcting exceptional situations instead of laboriously perusing the data trying to find the exceptions.

The Right Data Interpretation Strategy

Having someone onsite who knows how to read an oil analysis report and the operating conditions of the equipment is extremely important. With this skill set and the right strategy, the real value of oil analysis can begin to be realized.

Keep in mind that the rights of oil analysis are all equally important. No one specific right takes precedence over another. Each of these rights must be addressed and applied correctly. Otherwise, your time, effort and money will be wasted.

Trending Data

In the next iteration of the oil analysis program’s evolution, trending becomes a part of the analysis. No longer are you only looking at the report sitting in front of you, but now you are taking into consideration the history of the data. The best way to trend oil analysis data is to follow its movement visually using a standard trend plot.

Trending can quickly reveal the rate of change over time (slope on the plot) associated with a series of monotonic data points that might reveal a reportable condition. It can sometimes be concluded that if the rate of change is normal and constant (linear trend slope), the lubricant and machine conditions are equally normal and acceptable. However, abnormal or unhealthy conditions do not always produce steep trend lines.

Trending is a valuable tool to add to your oil analysis program. It is often overlooked in favor of a quick glance for abnormal results on a single, current report, but in doing so, much of the value of oil analysis is lost.

I’d like to propose a different type of trending. Instead of trending oil analysis reports from the same oil and same in-service machine, I’d like to see trending with a focus on the life cycle of the lubricant while onsite. This would require the first sample being taken when the drum arrives onsite. There are multiple reasons for this, including the example I’ll use going forward: contamination.

The effect that particle contamination has on machine reliability has been proven over and over in a number of case studies. It only makes sense that you use this knowledge to your advantage and employ cleanliness as a key performance indicator for your program.

Imagine a plot of ISO cleanliness over the life cycle of the lubricant. Usually the lubricant arrives too dirty for use in the equipment straight from a sealed drum, so it must be cleaned. This means your plot would start with a high point and slope down as you cleaned the lubricant while in storage.

If your plot levels out from there throughout its lifespan, you have done a good job at contamination control. However, if there is an upward spike when you take an oil sample after the machine component has been filled, you may want to check your handling practices.

If you notice the plot starts high as new oil, dives down after you clean it up, stays there until it is put into service in the component and then gradually climbs, this tells you that you have an ingression point at the point of use. When oil analysis data is used in this way, it makes it very easy to determine where you need to spend your time, money and energy to improve the process and also your machine reliability.

A number of scenarios could exist. The following are some of the most likely (as shown in the graph on the left):

  • A) The fluid arrives from the distributor dirty and is cared for in terms of contaminant ingression, but at no point in the process is the fluid ever cleaned. This results in high ISO particle counts in the machine, which ultimately affects reliability.
  • B) The fluid arrives dirty, and an effort is made to clean the fluid while in storage. It is kept clean during storage and is cleaned further upon application. The machine is modified to exclude particles but not remove them.
  • C) The fluid arrives moderately dirty and is cleaned. It is kept clean in storage, but the handling practices are lacking. Once the lubricant makes it to the machinery, the machine is modified to be able to remove the solid particles.
  • D) The fluid arrives clean but through poor storage and handling reaches the machine very dirty. The machine is then modified to be able to remove these newly ingressed particles.

Because of the effect particle contamination has on equipment reliability, you can see how this data can be used to help drive decisions on where in the process you need to focus. This is essentially where oil analysis earns its keep. It is a means by which you can make better informed decisions about your machinery, your practices and ultimately your business.

28% of lubrication professionals do not set cleanliness targets for machine reliability, according to a recent survey at MachineryLubrication.com
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