Reliability predictions focus on developing the appropriate reliability model suitable for existing data. A reliability assessment comes not only from testing the product itself but it is affected by information which is available prior to the start of the test. Bayesian methods are considered efficient in the reliability modeling field when the use of fault trees" and "reliability diagrams" are not possible. Bayes augment likelihood methods with prior information. Bayesian methods are capable of using a variety of information sources: statistical data, expert opinions, historical information, etc. to reach a probability distribution that is used to describe the prior beliefs about the parameter or set of parameters under study. This paper introduces a comprehensive review of using "Bayesian network approach" for modeling reliability and different methods and statistical distributions used in systems reliability studies."
Digital Object Identifier (DOI)
"Bayesian Statistics Application on Reliability Prediction and Analysis,"
Journal of Statistics Applications & Probability: Vol. 9:
1, Article 3.
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol9/iss1/3