This paper describes dynamic Valuation-Based System (VBS) for reliability assessment of systems under uncertainty. The reliability data and dependencies between components are represented using variables, sample spaces of variables, a set of valuations represented by probabilities, and basic probability assignments (bpas) that map sample spaces of sets of variables to the set of valuations. The uncertainties considered here are related to the states of components and their dependencies. The imprecise reliability of systems under uncertainty is estimated by an interval composed of upper and lower bounds. The proposed dynamic VBS approach is finally applied on a valve system and compared to the classical Bayesian Network approach.