DocumentCode :
764148
Title :
A new framework for part failure-rate prediction models
Author :
Wong, Kam L.
Author_Institution :
Kambea Ind., Manhattan Beach, CA, USA
Volume :
44
Issue :
1
fYear :
1995
fDate :
3/1/1995 12:00:00 AM
Firstpage :
139
Lastpage :
146
Abstract :
This paper presents a framework for developing part failure-rate models. It is a partial result of an effort sponsored by the US Air Force for the development of reliability prediction models for military avionics. Published data show that the existing reliability prediction methods fall far short of providing the required accuracy. One of the problems in the existing methods is the exclusion of critical factors. The new framework is based on the premise that essentially all failures are caused by the interactions of built-in flaws, failure mechanisms, and stresses. These three ingredients contribute to form the failure distribution which are functions of stress application duration (eg, aging time), number of thermal cycles, and vibration duration. The Weibull distribution has been selected as the general distribution. The distribution is then modified by the critical factors such as flaw quantities, effects of environmental stress screening, calendar-time reliability improvements, and vendor quality differences, to provide the part failure-rate functions. To provide credibility for the framework, only well published data and information have been used
Keywords :
Weibull distribution; avionics; failure analysis; military avionics; military equipment; reliability; Weibull distribution; accuracy; aging time; built-in flaws; calendar-time reliability improvements; critical factors; environmental stress screening; failure distribution; failure mechanisms; military avionics; part failure-rate prediction models; stress application duration; stresses; thermal cycles; vendor quality; vibration duration; Aerospace electronics; Environmental management; Failure analysis; Hazards; Life members; Prediction methods; Predictive models; Reliability engineering; Statistics; Thermal stresses;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/24.376540
Filename :
376540
Link To Document :
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