Bivariate Degradation Modeling Based on Gamma Process
نویسندگان
چکیده
Many highly reliable products have two or more performance characteristics (PCs). The PCs may be independent or dependent each other. If they are dependent, it is very important to find the joint distribution function of the PCs. In this paper, suppose that a product has two PCs and the PCs degradation can be governed by Gamma process. And the dependence of the PCs can be described by copula function. In order for estimating the product’s reliability as accurate as possible, the parameters of the two PCs and copula function can be estimated as a whole. The model in such a situation is very complicated and analytically intractable, hence very cumbersome from a computational viewpoint. So the Bayesian MCMC method is developed to this problem that allows the maximum likelihood estimator (MLE) of the parameters to be evaluated in an efficient manner. As a nice application of the proposed model, an illustrative example about fatigue cracks is presented.
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