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Hazardous events in process plants like the leakage of dangerous substances can result in severe damage, and such an event is often defined as the TOP event of a fault tree analysis (FTA) in a quantitative risk analysis. The TOP event probability can then be calculated if the basic events probabilities are provided. These probabilities are often determined based on generic reliability data which do not necessarily reflect the operational and environmental characteristics of a plant of interest. This paper presents an approach based on Bayesian network (BN) analysis to explicitly include experience data collected during the plant operation to make the generic probabilities more plant specific. The approach is illustrated via a pressure vessel containing a toxic substance in an Ammonia production plant. In this case study, the failure rate distribution in the BN is updated as the new information becomes available during plant operation. The results show that the suggested approach effectively reflects the operating experience of a specific plant.