A0249
Title: Likelihood inference for one-shot device testing under frailty models
Authors: Man Ho Ling - The Education University of Hong Kong (Hong Kong) [presenting]
Abstract: A device that performs its intended function only once is referred to as a one-shot device. The actual lifetimes of one-shot devices under life tests cannot be observed, and thus the lifetime information under test is very limited. In addition, one-shot devices often consist of multiple components that could cause the failure of the device. The components are coupled together in the manufacturing process or assembly, resulting in the failure modes possessing latent heterogeneity and dependence. Frailty models facilitate an easily understandable interpretation of the dependence between components. However, finding the maximum likelihood estimates of frailty models based on completely censored data is challenging. An efficient expectation-maximization algorithm is presented to find the maximum likelihood estimates of model parameters, on the basis of one-shot device testing data with multiple failure modes under a constant stress accelerated life test, with the dependent components having exponential lifetime distributions under gamma frailty. The maximum likelihood estimate and confidence intervals for the mean lifetime of the k-out-of-M structured one-shot device under normal operating conditions are also discussed. The performance of the proposed inferential methods is finally evaluated through Monte Carlo simulations.
