An accident model based on fault tree analysis was developed and applied to analyze the recurrence of undesired reactions producing popcorn polymers in the overhead condenser of an industrial butadiene distillation column. The modeling framework incorporates reliability data associated with asset integrity and human performance along with data on selected process variables. These variables, i.e., pressure, feed velocity and temperature of the condenser, which were identified from root cause analysis of the incident provided dynamic contributions to the model, and were represented in the form of Weibull distribution functions. The results obtained proved the potentials of the proposed methodology. Based on the case study considered, operating pressure was identified as the most influential process variables that needed closer monitoring. The methodology provides an opportunity for risk management to be implemented dynamically to facilitate maintenance plan and management of change.