Respectfully, I must countermand your disagreement. ... Sorry but I had to push back on that part of your disagreement- too much evidence to the contrary.
Due to character limits, I'll have to address my answer in two parts ... Two replies, as it were, from one answer.
My apologies if I misunderstood your initial comment I quoted; I took it as an inference that you thought UOAs were essentially not a good predictor of when to do something for a major maintenance event.
I'll defend what I claimed, but perhaps it's not germane to what your intent was. So for that I again apologize.
UOAs are not perfect; if we can agree on that, it's a good starting point.
But UOAs are most certainly useful tools which can impart information that is helpful, very much so, to understanding wear in both normal and abnormal senses.
First I'll speak to when things go badly:
As for macro events of impending catastrophe, there are plenty of anecdotal stories well documented where UOAs didn't pick up on the looming doom, and bad things occurred. But there are also plenty of anecdotal stories where UOAs did in fact pick up wear metal trends that ended up being a engine-life-saving (or at least life-altering) tid-bit which saved an engine from demise because the UOA showed a wear trend far outside of the "norm", and that alert was heeded, led to mechanical repair rather than mechanical demise; plenty of Blackstone examples in their newletters.
and the list can go on ...
What I would offer here is that UOAs will never catch every single issue, for a variety of reasons. But they most certainly do have the ability to detect things going wrong which, if caught soon enough, can lead to a major mechanical maintenance decision that might save money. If you don't agree, then we'll have to agree to disagree. I've seen so many examples of this type of "salvation" that it cannot be ignored or denied; UOAs can provide good information which leads to a proper mechanical decision being made.
Now I'll speak to when things go well:
UOAs can be used as a confirmation that wear is well in order, and equipment is in good shape, and maintenance efforts can be deferred (typically interpreted as an OCI extension). The purpose of oil is not to exist for itself; it's there to reduce wear. All things that oil does (lubricate, clean, cool) are inputs to the desire output; that of wear reduction. There are a bazillion examples of lubes doing a great job at this; countless UOAs which confirm that wear rates in a piece of equipment are well in line.
here's a condensed version of my point:
https://www.machinerylubrication.com/Read/30383/engines-oil-analysis
Using OAs to track lube health is OK, but it's only giving a prediction of when things might go wrong. But using OA to track trends in wear metals not only will likely indicate a potential wear-related failure, but also help narrow the focus as to what you might be looking for (Pb, Cu, Fe, Cr, Al can all give indication as to what component(s) might be failing). There is no ability of FP, vis, soot or fuel which will tell you what component is at risk, but the metals surely will! In other words, UOAs give us a two-pronged approach to understanding the overall symbiotic relationship between lube and equipment. UOAs will tell us the direct health of the lube, but that is only an indication that something might go wrong in the future (vis gets too thin; FP way high from excess fuel; soot too high) all simply imply that wear is likely to escalate soon. But if you see a trend in metals shifting, that's the actual evidence that the event is occurring!
Side bar - we'll probably agree that no OA is ever going to discern an acute failure; it's not going to discern a con-rod snapping from over-rev conditions, or a block cracking from thermal stress, etc ... UOAs are good at tracking chronic issues; those which develop over time. This is both a benefit and a limitation of the tool, and speaks to what I was illuminating in my initial comment about how/why to use UOAs, and what they can and cannot tell us.
There is a very interesting article by Fleetguard called "Differentiating Filter Performance by Oil Analysis Results". At face value, it would seem to prove that UOAs won't track the differences in filter efficiency and therefore a knee-jerk reaction is to assume that UOAs are not of value. But that totally misses a very fundamental concept ... The presumption is that there is a wear differential occurring and the UOA is missing it. Did it ever occur to the authors that the reason there's no ability to differentiate filter efficiency is because the physical differences in filters is not able to manifest into a wear differential in the first place? In other words, what the UOA data is telling them is that the effect of filtration is moot at certain OCI intervals. Their presumption is flawed; they believe the UOA is missing (not detecting) a difference, when the reality is that the UOA is telling them there exists no difference, when it comes to the filtration chosen combined with the OCI interval selected. This is just one example of misleading conclusions which taint people's view of UOAs.
SAE 2000-01-0234 (which I often refer to as the bus-study) shows a good correlation between PCs (particulate counts) and UOA wear date (Fe wear). They track many attributes of the lube, and show a good relationship between engine wear and contamination. It's an older study, and has lost some of it's relevance due to outdated engine designs, but it's a good example of how wear is easily tracked in UOAs.
SAE 2007-01-4133 shows how wear rates actually decline over fairly long OCIs. There is typically an elevated wear rate at the front end of an OCI, then it slowly drops as the miles pile up and the wear stays near-steady; effectively resulting in a declining wear rate. They use multiple methods of wear analysis (proton bombardment; electron spectroscopy; infrared reflection absorption). These are very finite, lab-intensive tests which the average BITOGer will not have cost-effective access to. But UOAs are very affordable, and they echo the exact same story for most all applications. The "normalcy" article I linked above clearly shows how UOAs repeatedly confirm that wear metals in UOAs exhibit the exact same phenomenon (that of wear escalation at the front end of an OCI, and subsequent deescalation across longer OCIs) as did the very expensive other methodologies. It's pretty hard to ignore what amounts to (literally) tens of thousands of UOAs showing the exact same effect in wear metal data. I guess one can choose to ignore the facts, but I accept them for what they are. UOAs are a reliable means to track wear which is shown to exhibit the exact same trends using far different equipment for analysis. In short, different methods of tracking wear come to the same conclusions; not by accident by by convergence of conclusions. While I would agree that UOAs have not been proven to be as accurate, they most certainly do exhibit a high degree of sensitivity tracking "normal" wear; completely echoing the other more expensive methods of doing so.
continued in next post ...