For those of us within the maintenance and reliability industries, we would have come across the topic of oil analysis as a method to monitor the health of the oils in machines. This monitoring method has been around for decades but is it still relevant with all of the new, shiny gadgets and technologies that we have today? In this article, we will explore some of the benefits of oil analysis, how it compares to other technologies and why we still need it today.

What is oil analysis?

For those not familiar with oil analysis, it can be likened to performing blood tests for the human body. Oil in our machines is often compared to the blood in our bodies. Blood circulates throughout the body taking important blood cells with food and oxygen in it to the various organs, similarly oils follow this behaviour. However, oils transport additives which provide varying functions including reducing wear or friction or even preventing corrosion or oxidation to name a few.

When performing a blood test, we can test for a few things; the overall condition of the organs or we can test for specific things such as the presence of bad cholesterol. With oils, we do a very similar practice where we can test for the overall health of the machine or pinpoint exact components and look for distinct changes which are reflected in the characteristics of the oil.

Basically, oil analysis can help you to determine the condition of your oil (if it is degrading or if the additives have depleted such that it no longer protects the equipment) and the health of your asset as the oil can reflect if there is wear occurring in the components. As such, it can provide very useful information to help operators and maintenance personnel to plan effectively for any type of maintenance to be done on the components.

Why oil analysis?

The P-F curve is one that is used throughout reliability to demonstrate the point at which a component is expected to have a functional failure. There are many variations of the PF curve, and different monitoring technologies can be placed in specific orders accordingly. However, it remains dominant that oil analysis is among the top three techniques used for early detection of failure.

Oil analysis can be used to detect the presence of contaminants, metals and other molecules at a microscopic level and quantify these appropriately. Most OEMs (Original Equipment Manufacturers) publish their acceptable standards for various tests (usually standardized tests by some accredited body such as ASTM) and have these available to laboratories around the world. When an oil analysis test is performed (as per the stipulated standards), the lab will compare the actual values to the expected values (from the OEM) and then provide some guidance to the user on possible steps forward.

Every lab will have a specific format for reporting the results of your oil analysis (similar to the labs for reporting on blood samples). Typically, the actual value is shown and then there may be an expected range for the various characteristics or just an indication of whether the actual value falls outside of the range (on the higher or lower end of the scale).

 (Bureau Veritas, 2017) gives an example of a report and all of the variables involved here: https://oil-testing.com/wp-content/uploads/2017/11/BV_Understanding-An-Oil-Analysis-Report_FINAL_11_8_2017.pdf

While this is their reporting standard, other labs will have a different format, but the tests will all conform to the same internationally recognized standard. As such, if oil is tested in the United States (as per a particular standard) and then tested in Italy (as per the same standard) then there can be some comparisons of these results. However, one must also be aware of the types of instruments being used and their calibration as this can account for slight differences in test results.  As such, oil analysis provides a global standard for which equipment performance can be compared across regions.

Oil analysis vs other technologies

Just as oil analysis is similar to blood testing, we can think of our bodies as a critical machine with various components which need to be monitored. If we get a fractured bone, a blood test will not help us to assess if the bone is broken or can be repaired. In this case, we may need an x-ray. Similarly, with machines, there are various types of tests to determine different aspects to be monitored.

Typically, oil analysis can provide the operator with insight into whether there has been any internal damage to the equipment in the form of wear particles which can be quantified. As with most condition monitoring methods, being able to trend the patterns over time helps the operators to identify if wear is occurring at an increased rate or whether the oil is degrading.

On the other hand, other technologies such as vibration analysis or ultrasound analysis or even thermography are not able to detect the presence of molecules. These other types of analyses focus on alignment, or other mechanical issues as they occur and can trend them over time. However, oil analysis can accurately detect the presence or absence of contaminants or additive packages which could affect the health of the oil and by extension that of the machine.

Oil analysis should not be used as the only technology in your condition monitoring artillery. Other technologies can be used alongside oil analysis to provide the user with a more comprehensive overview of the health of the asset. For instance, if the oil analysis discovered high wear, the next step would be to identify where the wear was coming from. Perhaps in this case, one of the other technologies could identify a misalignment or other mechanical issue which could be the source of this wear. Thus, these technologies should be used to work together to achieve better reliability for their asset owners.

Is Oil Analysis still relevant today?

With the many advancements in Artificial Intelligence, Machine Learning and the advent of countless different sensors on the market, the question arises, “Is Oil Analysis still relevant today?”. Granted that these advancements have significantly transformed the industry, we need to recognize that they are here to help evolve what we already do and not necessary replace it.

These advancements build upon the foundations of the techniques of oil analysis. With artificial intelligence and machine learning, we can train models to interpret oil analysis data and trigger alerts accordingly but there should always be a human present to overview these. In the real world, not every situation has occurred or been recorded yet hence the models do not have that particular data to learn from nor can they make decisions about it since it simply doesn’t exist in their “brain”.

Humans can “think outside the box” and formulate patterns or trends which may not be triggered by the models simply because these models have not been taught these patterns. Hence it is important to always have a human in the loop and not rely solely on these models especially when million-dollar decisions can be negatively initiated with the wrong interpretations.

Lately, sensors have gained more traction and a wider adoption as they can be integrated into warning systems to alert users to potential deviation from known characteristics of the oil. However, as noted above, sensors rely on data sets to compare the information and on some form of capacitance which must be converted into a signal before it can be interpreted.

With lab equipment performing the actual tests, there is a higher rate of accuracy plus the added advantage of having humans review the results for discrepancies before sending off the report. While sensors can be the first warning system for some users, lab equipment should be utilized for those more precise tests which require a higher level of accuracy.

In essence, oil analysis remains very relevant today. However, it has significantly evolved over the last few decades. Today, oil analysis can achieve a higher efficiency level with the integration of the advancements in technology (AI, machine learning and sensors) and other available monitoring technologies. Together, these should all be used to create a greater impact on improving the reliability of the machines.

References

Bureau Veritas. (2017). Understanding an Oil Analysis Report. Retrieved from Bureau Veritas: https://oil-testing.com/wp-content/uploads/2017/11/BV_Understanding-An-Oil-Analysis-Report_FINAL_11_8_2017.pdf

Author:

Sanya Mathura, REng, MLE

Founder, Strategic Reliability Solutions Ltd

Sanya Mathura is a highly accomplished professional in the field of engineering and reliability, with a proven track record of success in providing solutions to complex problems in various industries. She is currently the Managing Director of Strategic Reliability Solutions Ltd, a leading consulting firm that specializes in helping clients improve their asset reliability and maintenance practices.

Sanya holds a Bachelor's degree in Electrical & Computer Engineering as well as a Masters in Engineering Asset Management from The University of the West Indies and has over 15 years of experience in the industry. She has worked with several well-known companies and has been recognized for her exceptional work in the field of reliability and lubrication engineering. Her expertise in developing and implementing asset management strategies, risk assessments, and root cause analysis has earned her a reputation as a subject matter expert.

As the head of Strategic Reliability Solutions Ltd, Sanya leads a team of highly skilled professionals who provide a wide range of services to clients across various industries, including oil and gas, manufacturing, and transportation. Under her leadership, the company has expanded its services and is now recognized as a leading provider of reliability engineering services in the industry across the globe.

In addition to her work at Strategic Reliability Solutions Ltd, Sanya is an active member of several professional organizations, including the International Council for Machinery Lubrication and writes technical papers for several organizations. She is also a sought-after speaker and has presented at various conferences and seminars on the topics of reliability engineering and lubrication. She is also an avid advocate for women in STEM.