Quantitative risk assessment is methodology based on calculating probabilities and frequencies of sequential events using Boolean algebra, and it is normally used to perform safety assessments for complex interacting systems. Although quantitative risk assessment has been commonly used in aerospace and nuclear industries, it can also be used for quantifying economic risk and for estimating possibilities of potential production losses in a petrochemical or a manufacturing plant. In developing quantitative risk assessment models for petrochemical plants, component failures as well as human (operator) errors are taken into consideration in developing the plant's fault-tree logic, in which is used to predict probabilities of future plant upsets. This paper shows how the quantitative risk assessment can be used to rank the economic importance of the production units in a refinery for prioritizing maintenance activities. In addition, two case studies are compared to demonstrate how a quantitative risk assessment model can be used as an invaluable tool in process design optimization. The quantitative risk assessment methodology developed in this work relates production losses to the performance of the major components and the process design. This application of the quantitative risk assessment provides a basis for the risk-informed decision-making and optimizing allocation of plant resources in support of plant operation and maintenance activities.