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Manufacturers are required to demonstrate products meet reliability targets.A typical way to achieve this is with reliability demonstration tests (RDTs),in which a number of products are put on test and the test is passed if atarget reliability is achieved. There are various methods for determining thesample size for RDTs, typically based on the power of a hypothesis testfollowing the RDT or risk criteria. Bayesian risk criteria approaches canconflate the choice of sample size and the analysis to be undertaken once thetest has been conducted and rely on the specification of somewhat artificialacceptable and rejectable reliability levels. In this paper we offer analternative approach to sample size determination based on the idea ofassurance. This approach chooses the sample size to answer provide a certainprobability that the RDT will result in a successful outcome. It separates thedesign and analysis of the RDT, allowing different priors for each. We developthe assurance approach for sample size calculations in RDTs for binomial andWeibull likelihoods and propose appropriate prior distributions for the designand analysis of the test. In each case, we illustrate the approach with anexample based on real data.

Assurance for sample size determination in reliability demonstration testing