Title :
Bayesian Confidence Limits for the Reliability of Mixed Exponential and Distribution-Free Cascade Subsystems
Author :
Springer, Melvin D. ; Byers, James K.
Author_Institution :
Department of Industrial Engineering, University of Arkansas, Fayetteville, Ark. 72701.
Abstract :
The problem treated here is the theoretical one of deriving exact Bayesian confidence intervals for the reliability of a system consisting of some independent cascade subsystems with exponential failure probability density functions (pdf) mixed with other independent cascade subsystems whose failure pdf´s are unknown. The Mellin integral transform is used to derive the posterior pdf of the system reliability. The posterior cumulative distribution function (cdf) is then obtained in the usual manner by integrating the pdf, which serves the dual purpose of yielding system reliability confidence limits while at the same time providing a check on the derived pdf. A computer program written in Fortran IV is operational. It utilizes multiprecision to obtain the posterior pdf to any desired degree of accuracy in both functional and tabular form. The posterior cdf is tabulated at any desired increments to any required degree of accuracy.
Keywords :
Art; Assembly systems; Bayesian methods; Density functional theory; Distribution functions; Failure analysis; Probability density function; Reliability theory; Statistical analysis; System testing;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.1971.5216068