The Bayes Anlysis Of The Fuzzy Reliability

Reliability ia one of the most important indices to evaluate the quality of product. It hasbecome a most popular research direction. With the development of research, peoplebegin to realize that there exist not only randomness but also fuzziness in practicalproblems. So people begin to study fuzzy reliability. The theory and method of fuzzyreliability are not perfect. The paper has studied several aspects of fuzzy reliability asfollows:For the definition of fuzzy safety state is different,the calculation of fuzzy reliability isdifferent under different condition. A simple and practical method,to define membershipfunction of fuzzy event denoted by generalize fuzzy strength,is developed in the paper.Then fuzzy reliability optimization model is developed.The most efficient means to analyse the reliability of small sample is Bayes methodbecause it takes full use of prior information. The theory of fuzzy Bayes reliabilityprediction is not perfect. Based on current research resylts,a systematic method of Bayesreliability prediction is developed.Parameter prediction is very important for reliability estimation of zero failure data. Forthe question of poor stabilization in conventional linear regression equation,it is usuallythe impoved by a weighted coefficient. The fuzzy weight is put forward,and the forseveral life distribution models,estimated equation of failure rate and the reliability aregiven. Due to the fact that failure probability has large effect for the estimated value,theBayes estimation is given which bases on decrease function.A Bayesian approach to multiple fuzzy hytheses testing is put forward. Given theBayesian rule to multiple fuzzy hypotheses testing for the parameter of several lifedistribution models,and given the if and only if condition to one fuzzy hypotheses.