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Nowadays, complex manufacturing processes have to be dynamically modeled to estimate their reliability. Moreover the results computed with classical methods need to be reinforced by managing the uncertainty. To address these difficulties, this paper presents a new method for modeling and analyzing the system reliability based on dynamic evidential networks (DEN). This method allows modeling the influence of time and uncertainty on the failure and degradation of the system. The DEN graphical structure provides an easy way to specify the dependencies and, hence, to provide a compact representation of the system based on the Dempster Shafer theory. In addition, the DEN formalism is associated to simulation tools that enable an efficient processing for the models. A small system is used to compare the reliability estimations obtained by the proposed DEN model and those obtained by the classical Markov Chain.