In this paper I shall lay out in a detailed way the procedure of representing a fault tree through binary decision diagrams. In addition to that I shall show how highly important quantitative fault tree parameters can efficiently be derived from a fault tree representation. The fault tree representation through binary decision diagrams with the aid of efficient minimisation procedures results in a minimal disjunctive form, which corresponds to the initial fault tree. Out of these minimal forms by simple procedures all or only some combinations of basic events are determined, which are essential for the achievement of unwished top events. Beside the identification of unwished combinations of basic events, the representation through binary decision diagrams enables the determination of relevant empirical parameters for each elementary component (basic event). This procedure enables the establishment of the importance factor of every component e.g. risk increase factor, risk decrease factor, Fussel−Vesely importance factor, critical importance factor and others. The thesis also presents developed algorithms for the determination of importance measures for components as well as respective results for actual examples from the literature and praxis relating to parts of model fault trees for the nuclear power plant "Krško". It is particularly important to emphasize the advantages of such an approach in the exact quantitative calculation of fault trees compared to alternative representations which bring only approximate results.