Interpreting the results of an oil analysis, an entire page filled with numbers, can appear to be a formidable task to the untrained eye. But like every other complicated task, by breaking it down into manageable parts, the job can be simplified, which makes the outcome more accurate.
The best approach to diagnosing an oil analysis is to group the tests according to the category of the analysis they represent. The three aspects of oil analysis are:
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condition of the fluid, also known as the fluid properties analysis
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fluid contamination
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machine wear
I always emphasize this approach in the training seminars I teach, yet I still find that my students always have a strong urge to jump straight into the numbers and analyze them in the order they appear on the page. Page-order interpretation is a less-than- disciplined approach that complicates the situation, leading to wrong interpretation.
Grouping
Figure 1 illustrates the most commonly performed oil analysis tests, and the categories each test serves.
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Figure 1. Oil Analysis Tests
Figure 1 proves the majority of the tests tend to overlap in two or more categories. Take, for example, the particle count. Its primary function is to quantify and qualify solid particulate contamination in the oil, but if we can establish by some means that the contamination is composed primarily of wear particles, then the particle count can also be used as a wear-analysis tool. Therefore, because there may be some ambiguity in categorization, each test should still be grouped into the category it best serves. Using the tests in Figure 1, I would group them as:
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Oil condition: viscosity, AN/BN, elemental analysis (additives)
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Oil contamination: particle counting, moisture analysis, patch test, flashpoint, elemental analysis (contaminants)
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Wear: wear (ferrous) debris, analytical ferrography, elemental analysis (wear)
Elemental analysis should be seen as a grouping of individual tests, typically 20 to 30, rather than just a single test.
Varying Results
Another reason to analyze each category separately is that one category may have a critical status while another may appear normal. For example, in a misalignment situation it is possible for wear to be critical while oil condition is normal. Or, there could be a critical contamination problem, yet oil condition and machine wear are normal (this might occur in an oil sample taken immediately after a filter was dumped). A good oil analysis interpretation will differentiate between the status of each of the three categories. If a report has an overall status, it should reflect that of the worst-performing category.
Analysis, Diagnosis and Prognosis
Once the tests have been grouped into three categories, each group should be analyzed. You can make a diagnosis of the status of the category in question. The sample diagnosis is a summation of each of the categories. Statements in the diagnosis might appear as: "Oil condition is acceptable"; "Moisture contamination has increased since the last sample and has become actionable"; or "Machine wear appears normal." Of course, more than one category might be addressed concurrently: "An increased particle count in conjunction with the increased elemental iron and ferrous density indicate an abnormal wear situation is developing," but such a statement can be made only after considering each of the categories.
Once the diagnosis has been made it's time to make the prognosis. The prognosis is a statement of the actions needed to correct an abnormal situation. This is the ultimate goal of oil analysis, and where the experience of the diagnostician and his or her familiarity with the machines comes into play. The prognosis can be accurate only if an accurate diagnosis has been made, and an accurate diagnosis can be made only if the analyses have been correctly categorized and analyzed.
Using a compartmentalized approach to your interpretations will help to improve accuracy and increase the value of your oil analysis program. Try it. It's how the experts do it.
