A BAYES METHOD FOR ASSESSING PRODUCT-RELIABILITY DURING DEVELOPMENT TESTING

A fully Bayes approach is presented for analyzing product reliability during the development phase. Based on a Bayes version of the Barlow-Scheuer reliability-growth model, it is assumed that the product goes through a series of test/mmodification stages, where each product test yields attribute (pass-fail) data, and failure types are classified as fixable or nonfixable. Relevant information on both the failure probabilities and the reliability-growth process is used to motivate the prior joint distribution for the probability of each failure type over the specified range of testing. Results at a particular test-stage can be used to update the knowledge about the probability of each failure type (and thus product reliability) at the current test-stage, as well as at subsequent test-stages, and at the end of the development phase. The relative ease of incorporation of prior information as well as the tractability of the posterior analysis is accomplished by using a Dirichlet distribution as the prior distribution for a transformation of the failure probabilities. In so doing, the posterior distribution of all relevant quantities can be expressed as mixtures of beta (or Dirichlet) distributions. The theory unifies the existing Bayes approaches in attribute reliability-growth modeling.