Fuzzy Bayesian Belief Networks Method on Risk Assessment of EPC Pipeline Project

Abstract

Subsea gas pipeline projects are experiencing significant technical and managerial challenges across Engineering, Procurement, and Construction (EPC) phases. To address the challenges, effective risk management in the early project phases is essential to mitigating cascading failures that cause significant schedule delay and cost overrun. Therefore, this study aimed to apply the Fuzzy Bayesian Belief Networks (FBBNs) method to model risk assessment during EPC phases. The findings showed that FBBNs made it possible for a new way to evaluate risks, find interdependencies, and guess what would happen next, which created a strong framework for reducing risk. Based on probabilistic analysis as supported by expert elicitation, risks from the early phase of engineering and procurement showed high probabilities of occurrence, including Incompetent Personnel, Project Mismanagement, Unsupportive Stakeholder, Corruption, and Design Inaccuracies. A significant impact was also observed on Construction Rework, Material Quantity Increase, Construction Delay, and Cost Overrun. The results showed the importance of addressing systemic issues early in the EPC project lifecycle, emphasizing personnel competency, design accuracy, strategic and project management planning, procurement management, stakeholder management, and constructability preparation to reduce vulnerabilities. This integrated method aimed to enhance accuracy predictions by determining causal risk probability relationships in high-risk offshore environments of EPC subsea gas pipeline projects. Doi: 10.28991/CEJ-2025-011-03-013 Full Text: PDF