Zhengqiang Pan

TL;DR: This paper proposes to use a bivariate Birnbaum–Saunders distribution and its marginal distributions to approximate the reliability function of a product that has two dependent performance characteristics and that their degradation can be modeled by gamma processes.

TL;DR: In this paper, the authors consider a product with two performance characteristics and the degradation paths of these performance characteristics can be governed by a Wiener process with a time-scale transformation, and the dependency of the performance characteristics is described by a copula function.

TL;DR: The Bayesian Markov chain Monte Carlo (MCMC) method is developed here for this model for obtaining the maximum likelihood estimates (MLEs) efficiently and a simulated example is presented along with the associated computational results.

TL;DR: The Bayesian Markov chain Monte Carlo (MCMC) method is applied for multiple-steps step-stress accelerated degradation models based on Wiener and gamma processes to obtain the maximum likelihood estimates (MLEs) efficiently and some computational results obtained from the implementation are presented.

TL;DR: Reliability model of the degradation products with two performance characteristics based on gamma processes are introduced, and the corresponding SSADT model is presented under the constraint of total experimental cost.