Accelerated Life Tests of a Series System with Masked Interval Data Under Exponential Lifetime Distributions

• Main Authors: Tsung-Ming Hsu, 許琮明
• Other Authors: Tsai-Hung Fan
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/24428434414768060510

碩士 === 國立中央大學 === 統計研究所 === 98 === In this thesis, we consider a system of independent and non-identical components connected in series, each component having a Exponential life time distribution under Type-I group censored. In a series system, the system fails if any of the components fails, and it may only be ascertained that the cause of system failure is due to one of the components in some subset of system components, so called masked data. We discuss the step-stress accelerated life testing in which the mean life time of each component is a log-linear function of the levels of the stress variables. The maximum likelihood estimates via EM algorithm is developed for the model parameters with the aid of parametric bootstrap method to estimate the resulting standard errors when the data are masked. Subjective Bayesian inference incorporated with the Markov chain Monte Carlo method is also addressed. Simulation study shows that the Bayesian analysis provides better results than the likelihood approach not only in parameters estimation but also in reliability inference under normal condition for both the system and components.