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

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

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Publication Details

Journal
Civil Engineering Journal
Published
2025-03-01
DOI
https://doi.org/10.28991/cej-2025-011-03-013
Citations
2
Primary Topic
Structural Integrity and Reliability Analysis
Type
article
Field-Weighted Citation Impact
1.43
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article

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

Yusuf Latief, Bambang Trigunarsyah, Muhammad Yusuf, Ayomi Dita Rarasati et al.
2 citations
Civil Engineering Journal
Structural Integrity and Reliability Analysis
1.43
article

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

Yusuf Latief, Bambang Trigunarsyah, Muhammad Yusuf, Ayomi Dita Rarasati, Naufal Budi Laksono
article en
2 citations

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

Civil Engineering JournalVol. 11(3)
University of Indonesia (ID), MIT University (MK), RMIT University (AU)
Openalex Percentile: Top 22%
Structural Integrity and Reliability Analysis
1.43
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