Reliability prediction for electronic components: Difference between revisions

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A [https://en.wikipedia.org/wiki/Prediction prediction] of reliability is an important element in the process of selecting equipment for use by [[telecommunications]] [[service providers]] and other buyers of [[electronic equipment]]. Reliability is a measure of the [[frequency]] of equipment failures as a function of time. [[Reliability]] has a major impact on maintenance and repair costs and on the continuity of service.<ref>Terry Donovan, Senior Systems Engineer Telcordia Technologies. Member of Optical Society of America, IEEE, "Automated Reliability Prediction, SR-332, Issue 3", January 2011; "Automated Reliability Prediction (ARPP), FD-ARPP-01, Issue 11", January 2011</ref>

Every product has a [[failure rate]], λ which is the number of units failing per unit time. This failure rate changes throughout the life of the product. It is the manufacturer’s[[manufacturer]]’s aim to ensure that product in the “[[infant“infant mortality]] period” does not get to the [[customer]]. This leaves a product with a useful life period during which failures occur randomly i.e., λ is constant, and finally a wear-out period, usually beyond the products useful life, where λ is increasing.

==Contents==

* Definition of Reliability

* MTBF and MTTF

* Importance of Reliability prediction

* References

== Definition of reliability ==

A practical definition of reliability is “the probability that a piece of equipment operating under specified conditions shall perform satisfactorily for a given period of time”. The reliability is a number between 0 and 1.

== MTBF and MTTF ==

[[MTBF]] (mean operating time between failures) applies to equipment that is going to be repaired and returned to service, [[MTTF]] (mean time to failure) applies to parts that will be thrown away on failing. During the ‘useful life period’ assuming a constant failure rate, MTBF is the inverse of the failure rate and the terms can be used [[Interchangeable|interchangeably]]

== Importance of reliability prediction ==