There is a probability of failure related to a particular engine, oil/OCI, and driving style. This is vastly over simplified since every instance is unique. Nevertheless there is a statistical concept used to predict life expectancy called MTBF (mean time between failure) which is helpful to understand the impact of certain vehicle maintenance.
MTBF is a calculation which can be/is done by the manufacture based on all the failure modes observed and analysis of failure mechanisms. Of course two of these variables are engine oil and OCI (oil change interval)
Let’s assume a manufacture sets oil/OCI to achieve MTBF that is cost effective* to say 120K miles. By definition MTBF means 50% fail before and 50% after MTBF. So in this case, half of the engines are expected to last 120K and half fail based on recommended service interval. Nevertheless the average life expectancy is 120K.
There is a probability distribution which is calculated from the failure modes called "Standard Deviation" (aka S.D. or sigma). It is used to predict the probability of failure relative to the average or MTBF.
Statistically +/- one SD from the MTBF covers 67% of failure population. Lets say SD=20K miles, then using above, 67% of engines likely to fail between 100K and 140K miles.
Two SD covers 97% probability. Three SD 99.6%. So in this case there is 3% probability that you'll fail before 80K or exceed 160K. Assuming 'normal' distribution, there is a 1.5% chance fail before 80K and 1.5% chance fail after 160K. You can see how this is useful to predict likely warranty costs in large sample size.
Now put aside what actual MTBF or SD predicted for your engine since you can not control that. These can be calculated by the manufacture and may be set to minimize owner cost* over expected vehicle life. What you can do is change the probability of your failure by changing oil, OCI, or other factors, such as driving habits.
*Cost effectiveness may assume dealer changes that may be more expensive than DIY.
This would lead to longer OCI recommendation. Sure we can service more often but there is a price to pay and is it worth it compared to the future cost of repair.
For myself, I use most vehicles between 140-200K so my target MTBF is much longer. At the same time I want to reduce SD or surprise factor ! This implies an improved service over the manufacture’s recommendation. Two things to look at is improved oil or reduced OCI.
Ideally there is no increase in oil consumption as vehicle ages. Unfortunately it takes awhile to determine this and after damage is done the best you can do is stabilize it at that point.
My current example is a 2005 Ford Duratec 3L engine. Factory spec is MC 5W20 blend with 5K OCI (normal) and 3K OCI (severe duty). Warranty requires 5K OCI minimum.
I used MC blend until 18K miles except one run of dino after factory fill. OCI during this time was 3K. I wanted short OCI until about 20K. At that point I changed to a GrpIII synth (PPqt) and extended the OCI to 5K. I feel this is conservative but is a cost effective way to increase engine life probability.
Each situation is different but the concept is the same; better oil with reduction in OCI done in a cost effective manner can extend life, reduce uncertainty, and reduce overall ownership cost.
MTBF is a calculation which can be/is done by the manufacture based on all the failure modes observed and analysis of failure mechanisms. Of course two of these variables are engine oil and OCI (oil change interval)
Let’s assume a manufacture sets oil/OCI to achieve MTBF that is cost effective* to say 120K miles. By definition MTBF means 50% fail before and 50% after MTBF. So in this case, half of the engines are expected to last 120K and half fail based on recommended service interval. Nevertheless the average life expectancy is 120K.
There is a probability distribution which is calculated from the failure modes called "Standard Deviation" (aka S.D. or sigma). It is used to predict the probability of failure relative to the average or MTBF.
Statistically +/- one SD from the MTBF covers 67% of failure population. Lets say SD=20K miles, then using above, 67% of engines likely to fail between 100K and 140K miles.
Two SD covers 97% probability. Three SD 99.6%. So in this case there is 3% probability that you'll fail before 80K or exceed 160K. Assuming 'normal' distribution, there is a 1.5% chance fail before 80K and 1.5% chance fail after 160K. You can see how this is useful to predict likely warranty costs in large sample size.
Now put aside what actual MTBF or SD predicted for your engine since you can not control that. These can be calculated by the manufacture and may be set to minimize owner cost* over expected vehicle life. What you can do is change the probability of your failure by changing oil, OCI, or other factors, such as driving habits.
*Cost effectiveness may assume dealer changes that may be more expensive than DIY.
This would lead to longer OCI recommendation. Sure we can service more often but there is a price to pay and is it worth it compared to the future cost of repair.
For myself, I use most vehicles between 140-200K so my target MTBF is much longer. At the same time I want to reduce SD or surprise factor ! This implies an improved service over the manufacture’s recommendation. Two things to look at is improved oil or reduced OCI.
Ideally there is no increase in oil consumption as vehicle ages. Unfortunately it takes awhile to determine this and after damage is done the best you can do is stabilize it at that point.
My current example is a 2005 Ford Duratec 3L engine. Factory spec is MC 5W20 blend with 5K OCI (normal) and 3K OCI (severe duty). Warranty requires 5K OCI minimum.
I used MC blend until 18K miles except one run of dino after factory fill. OCI during this time was 3K. I wanted short OCI until about 20K. At that point I changed to a GrpIII synth (PPqt) and extended the OCI to 5K. I feel this is conservative but is a cost effective way to increase engine life probability.
Each situation is different but the concept is the same; better oil with reduction in OCI done in a cost effective manner can extend life, reduce uncertainty, and reduce overall ownership cost.