A novel risk assessment approach using Monte Carlo simulation based on co-occurrence of risk factors: A case study of a petrochemical plant construction

Abstract

Nowadays, due to the development of technology as well as the occurrence of unpredictable events, it is necessary to address risk management as an important part of projects and businesses. In this paper, a novel approach based on Monte Carlo simulation is proposed for risk assessment, which considers the co-occurrence of risks. In this method, the output of extended and classic Monte Carlo simulations is employed for Co-Occurrence-based Risk Assessment (CORA) and prioritization. Also, the magnitude of uncertainty in each source has been determined using the new approach. In addition to identifying and analyzing the risks, the proposed model investigates possible relationships between risks and determines the type of risk-induced impact as either resonance or reduction. Also, a system dynamic model is applied to illustrate the relationships among the risks. Finally, this method is utilized for a petrochemical project. Five risks including temperature, rain, labor, cost, and inflation are considered in this project. Based on the numerical results, the most important risk is inflation. Also, there is a significant difference between the result of the proposed model and the model outcome, which had previously ignored the co-occurrence of risks. CORA helps managers consider all aspects of risks and make a better decision.