Piston engine reliability (questions for high time pilots and mechanics)

[Electric]

It seems like everyone that has more than 2000 hours in piston aircraft had at least one engine failure. Is that really the case?

I'm a fairly new pilot (170 hours) and it seems rather discouraging to know that if I plan on flying piston singles for a long time I should expect at least one deadstick landing in the future. Especially, considering that 1 out of 10 NTSB reports due to engine failure involves a fatality.

Would an engine that is well cared for vs the engine on a rental aircraft be significantly more reliable?

How well can you manage the risk of mechanical engine failure (not related to fuel starvation, contamination, vapor lock or induction icing, only talking bout mechanical failures.) during preflight or during maintenance?

Are those "mechanical" failures primarily due to negligence/poor maintenance, or its a truly random occurrence?

How helpful is mutli probe engine monitor in predicting otherwise unexpected power loss?

What can a renter (or perhaps an owner) do to significantly mitigate the risk of mechanical engine failure? (again talking about true mechanical failure, not fuel or induction icing related)

I don't mind taking risk, and I know that weather and stall/spin accidents take way more lives than engine failures. However, unlike stall/spin and weather accidents, engine failures can not be avoided by training; and at least at this point, to me engine failure seems like a random occurrence that is very likely to happen if you fly long enough. Which is why it's one of the very few things that makes me nervous.

Please advice, answers to the questions above would be appreciated, sorry for a long post.

 

[Jim Logajan]

Well, not sure my logic is correct, but how you described it, is how I arrived at the number.

The flaw in that number, is to asume it's a constant, and that everyone has an equal change of being the unlucky individual. We know that's not true.

We know for every 44,583 hours, someone dies. Let's turn it around, and make it a lottery. We are selling 44,583 tickets, and only one person wins.

If you only bought 1 ticket, you would have a 1/44,582 chance of winning. However if you bought 2,000 of them, you have a 4.5% chance of winning. This thought process is where I came to the number.

I realize it's flawed, but you have to come to a number somehow to quantify risk, so it's the one I chose

Your math is a reasonable approximation so long as the span of time you want to estimate for is small, but fails for larger spans. In your scenario buying all 44,582 tickets yields a 100% probability of winning. But you probably realize that you can fly 44,582 hours and not die.

The usual method (assuming equal probabilities for all hours, a generally invalid assumption) is to multiply together all the probabilities of the opposite result occurring, to get the net probability. So in one hour your probability of dying is 1/44,582 = 0.000022431 (0.0022431%). That means the probability of surviving that hour (the opposite result) is 1 - 0.000022431 = 0.999977569 (99.9977569%).

Your probability of surviving 2000 hours is 0.999977569^2000 = 0.9561 (95.61%) The opposite result of dying is 100 - 95.61 = 4.39%. Your result of 4.5% isn't far off.

But at 44,582 hours the probability of your surviving is 0.999977569^44,582 = 0.3679 (36.79%). The opposite result of dying is 100 - 36.79 = 63.21%. Your result of 100% dying is pretty far off, and the approximation method yields nonsense with any number over 44,582 hours.

Anyway, hope this helps for those whose recollection of statistics is rusty or wasn't something you ever had to learn.