Reliability model for dual constant-stress accelerated life test with Weibull distribution under Type-I censoring scheme

To inference the reliability of product at normal stress conditions, accelerated life test (ALT) is usually used to obtain failure information rapidly. However, most of the researches on ALT are focused on the statistical inference with single stress, which makes it difficult to gain accurate reliability through applying ALT method in single stress case. In this article, statistical inference is considered on dual constant-stress accelerated life test (DCSALT) model for the Weibull distribution with Type-I censored data. On the assumption that the Weibull distribution has constant shape parameter, and a log-linear acceleration model between its scale parameter and the test stress level combination. Using the profile maximum likelihood estimation (PMLE) method to estimate the unknown parameters in DCSALT model for Weibull distribution, and this process is completed by Newton-Raphson algorithm. Moreover, the observed information matrix is obtained in order to construct asymptotic confidence intervals of the unknown parameters. Finally, the numerical study is presented to illustrate the effectiveness of the maximum likelihood estimators (MLEs).