Used oil analysis — it’s a condition monitoring tool with a strange paradox. In my anecdotal experience across many industries, 90% of sites are doing used oil analysis. Lube techs the world over diligently take samples on a regular schedule, log the activity in a CMMS or spreadsheet, record key information about the sample, then post it off to a laboratory for analysis.
Quality varies — some sites are more conscientious about preventing sample contamination or ensuring that sample points are in appropriate locations. But most are at least attempting to collect regular data, and in today’s landscape of reliability best-practice, data is the new oil.
But this is where the story ends for most, which is sad because all the cost of a used oil analysis program is spent upfront: the cost of the sample bottle (which typically includes the analysis) and the time taken for the lube tech to perform their rounds, collect samples and post them. Unfortunately, when the results return, they’re typically filed away, never to be seen again. If there’s a red box, a work order might be generated to change the oil, but as the world moves to a paradigm of condition-based maintenance, it’s rare that I see oil analysis truly informing decision-making.
For many sites, this comes down to a lack of knowledge and lack of time. It’s understandable when workforces are shrinking, but processes are becoming ever more complex. Plus, a used oil analysis (UOA) report contains a lot of information that isn’t so easy to digest. How does one parse the data and determine what is important versus what is noise?
So here’s a tip. Next time your used oil analysis report comes back, take a minute to look at the results. Then at each test result, ask yourself, “why should I give a s---?”
Let’s illustrate with some examples:
Oxidation is often used as the primary indicator of lubricant condition. If oxidation is high, this is usually an indication to change the oil. But oxidation is not truly a measurement because it is a concept or process rather than physical property of the oil. Why should you give a s---? Oxidation of the oil produces radicals that promote polymerization (viscosity increases) and reactions with additives (additive depletion). We should investigate — has the viscosity, in fact, increased? Has Phosphorous decreased? Do the RULER results indicate a reduction in antioxidant levels? If the answer is no, then maybe no action is necessary because the lubricant condition is still satisfactory. There might also be an alternative explanation because not all oxidation tests are created equal. A test using the differential spectra method may yield a lower value than one resulting from JOAP.
What about wear metals? Does a high wear metal value automatically indicate poor machine health? Not necessarily. As the name suggests, we give a s--- about wear metal results because they typically point to the wear condition of the equipment. Wear is not a physical property; it is a process. Wear is a machine degradation mode, and degradation occurs over time. So wear metal results matter most when they are compared to previous results. For comparison, which of the following identical machines is wearing faster?
Most likely, it’s machine 2, even though the absolute values for the wear metals are lower than machine 1. The takeaway here is that we only give a s--- about wear metals when they are increasing because that indicates a degradation in the machine. The rate of change is more important than the value on the report.
How about high copper readings on a report? Do I give a s---? This question is very application-specific. For an engine oil sample, maybe yes, I really give a s--- because the main sources of copper are the crankcase bearings and oil coolers. Crankcase bearings are a very expensive and painful replacement job, so it’s important that the site can determine which of the two is the source of the high copper reading.
In other applications, the only potential source of copper may be the oil coolers, so the question takes on a different significance. Oil cooler copper loss can generally be caused by two different processes: corrosion or passivation. Passivation is a natural process when fresh copper comes into contact with the oil and is common when a new cooler has been installed. Some additives will exchange with the copper while depositing a layer of corrosion inhibitors — this is relatively harmless and a process that will decelerate as the exposed areas of fresh copper slowly disappear. On the other hand, corrosion is a nefarious process that can eventually cause a coolant leak into the lube oil system. Corrosion tends to accelerate over time as the acid number of the oil increases and creates a more corrosive environment.
Of the above two examples, we would really give a s--- about the accelerating trend. The decelerating trend? Not so much.
These are just a few examples, but there are countless others. Low phenols in a RULER test? We potentially don’t give a s--- if there are still amines remaining or if the lubricant formulation doesn’t contain any phenols to begin with. How about high soot? Soot particles are only really harmful when they agglomerate; check to see if they correlate with high wear metals because maybe the dispersants in the oil are reducing the impact of soot. The same goes for silicon. Low TBN in an engine oil? It’s just an additive — if TAN hasn’t increased, it might not be a big deal, but if TAN is increasing, then depleted TBN additives won’t be able to halt an increase in acid formation. High TAN? High acidity can be bad, but it is the result of high acid number (corrosion) that you really give a s--- about. So check the correlation with lead, copper and tin. Your lubricant should also be protected by corrosion inhibitors, so it’s possible that they’re still held in check.
Hopefully, with these examples, it’s been illustrated that one simple question can unlock a lot of insight. It certainly is not a panacea that will solve all your report interpretation woes; rather, it can triage used oil analysis results and trigger conversations about what really matters and has an impact on machine reliability.
And just in case it isn’t clear. S--- stands for stuff.