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A concept which is closely related to MTBF, and is important in the computations involving MTBF, is the mean down time (MDT). MDT can be defined as mean time which the system is down after the failure. Usually, MDT is considered different from MTTR (Mean Time To Repair); in particular, MDT usually includes organizational and logistical factors ...
The mean time between failures (MTBF, /) is often reported instead of the failure rate, as numbers such as "2,000 hours" are more intuitive than numbers such as "0.0005 per hour". However, this is only valid if the failure rate λ ( t ) {\displaystyle \lambda (t)} is actually constant over time, such as within the flat region of the bathtub curve.
In a system the mean time between outages (MTBO) is the mean time between equipment failures that result in loss of system continuity or unacceptable degradation.
This is the smallest time after the initial time t 0 that y(t) is equal to one of the critical values forming the boundary of the interval, assuming y 0 is within the interval. Because y(t) proceeds randomly from its initial value to the boundary, τ(y 0) is itself a random variable. The mean of τ(y 0) is the residence time, [1] [2]
Now the formulae do need to know MDTs to calculate MTBFs in general case (and vice versa), but that's a fact of life (the faster you repair parallel components - the less chances are for the whole system to fail, and IMO all the math models which assume that the time is discreet and everything is fixed on the next time slot - are significantly ...
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In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated.This can be thought of as a generalisation of many classical methods—the method of moments, least squares, and maximum likelihood—as well as some recent methods like M-estimators.
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