A fuzzy-bayesian model for risk assessment in power plant projects

Cost overrun in power plant projects is a global problem. Assessing potential risks at preliminary stage of the project is important to control cost overrun. Existing models are discovered as ineffective for assessing cost overrun risks in power plant projects due to two basic limitations- i) incapable to handle subjective biases in riskassessment and ii) complex relationship among the risk factors. A novel method based on the combination of fuzzy logic and Bayesian belief network has been developed, which can solve both drawbacks of the existing models and provides the best result for finding inherent risks in power plant projects. This model assists the project managers providing early warning to manage the critical risks. It also helps to reach a realistic budget considering the costs of potential and critical risks in the estimation process, which consequently reduces the cost overrun of power plant projects.