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Re: [OM] Are OM-2S Circuits Getting A Bad Rap?

Subject: Re: [OM] Are OM-2S Circuits Getting A Bad Rap?
From: "John A. Lind" <jlind@xxxxxxxxxxx>
Date: Mon, 12 Mar 2001 22:16:45 +0000
At 15:07 3/12/01, Frieder Faig wrote:
Have you ever wondered of MTBF-values ? Very comon as value for trstiness of computer disk drives. 500 000h live time for a hard drive?? Well it is not the time a drive will last between two repairs. It is a rahter theoretical value. Interesting is the reciprocal value, which is the likeliness your equipment will fail. Too sad, Ive no MTBF values for OM-2S circuits. But this MTBF may give an idea of reliability of (good) electronics.*)

Frieder Faig

Failures are randomly distributed around a mean life expectancy. This means my OM-2S may have a longer or shorter life span than someone elses . . . even with the same usage rate and care. (Excluded are failure inducing events such as dropping it.) If you were to study enough of them, you could build a probability distribution.

Other than mechanical wear which tends to "tighten" the probability distribution around a fixed life, the MTBF of most devices is modeled as an exponential distribution. It represents the lifetime of a device with a constant probability of failure and models most electronics fairly well. (Reliability studies often use a Weibull.) The attractiveness of the exponential distribution as a model is its inverse, a Poisson distribution. The Poisson can model the probability of how many failures will be encountered per unit of time (e.g., failures per year). None of these looks anything like a "normal" distribution (bell curve).

What does this mean (pun completely intended)?

Users would be interested in the exponential model of the MTBF as it would tell us what to expect for a lifetime, and how much the lifetime for one may vary for another.

OTOH, John H. and Clint, as repairers, would be interested in the Poisson model which, given an estimated population size, would tell them what to expect in failures per year (i.e. how much business they can anticipate as some percentage of all failures) and how much that could vary from year to year.

-- John


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