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, because of the advancement of technology and subsequently unpredictable events, it is important for addressing risk management as an important part of projects and business. In this paper, a novel approach based on Monte Carlo simulation has been proposed for risk assessment, which considers the co-occurrence of risks. In this method, the output of extended and classic Monte Carlo simulation is applied for co-occurrence-based risk assessment (CORA) and prioritization. Also, the magnitude in each source of uncertainty has been determined by a new approach. The proposed model investigates risk's relationship and determines the type of effect as resonance or reduction in addition to identifying and analyzing the risks. Also, a system dynamic model is applied to illustrate the relationships of risks. Finally, this method is applied to a petrochemical project. Five risks as 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 different between the result of the proposed model in comparison with model that ignore the co-occurrence of risks. CORA helps the manager to consider all aspect of risks and help them to have a better decision.

Risk assessment of medical devices used for COVID-19 patients based on a Markovian-based Weighted Failure Mode Effects Analysis (WFMEA)

“…First, they listed the risks and then identified the relation among these risks using system dynamic approach. Their results showed that the risks such as inflation, cost, temperature, rain, and labor are the most important risks [26].…”