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{{multiple issues|one source=February 2011|orphan=February 2011|refimprove=February 2011|wikify=February 2011}}
A prediction of
▲A prediction of [[reliability]] is an important element in the process of selecting equipment for use by [[telecommunications]] [[service provider]]s 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 aim to ensure that product in the “[[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.
== Definition of
A practical definition of reliability is “the
== 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 interchangeably
== Importance of
Reliability predictions:
:* '''Help assess the effect of product reliability on the maintenance activity and on the quantity of spare units required for acceptable field performance of any particular system.''' For example, predictions of the frequency of unit level maintenance actions can be obtained. Reliability prediction can be used to size spare populations.
:* '''Provide necessary input to system-level reliability models.''' System-level reliability models can subsequently be used to predict, for example, frequency of system outages in [[Steady state (electronics)|steady-state]], frequency of system outages during early life, expected [[downtime]] per year, and system availability.
:* '''Provide necessary input to unit and system-level
:* '''Assist in deciding which product to purchase from a list of competing products.''' As a result, it is essential that reliability predictions be based on a common procedure.
:* '''Can be used to set factory test standards for products requiring a reliability test.''' Reliability predictions help determine how often the system should fail.
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:* '''Can be used to set achievable in-service performance standards''' against which to judge actual performance and stimulate action.
The [[telecommunications industry]] has devoted much time over the years to concentrate on developing reliability models for electronic equipment. One such tool is the
The RPP views electronic systems as hierarchical assemblies. Systems are constructed from units that, in turn, are constructed from devices. The methods presented predict reliability at these three hierarchical levels:
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