Identifying and Modeling the Causes of Gas Pipeline Excavation and Piping Operation Accidents Using Bayesian Network (BN) and Fuzzy DEMATEL: Case Study on Trench Collapse

Aida  Naghshbandi; Omran  Ahmadi

doi:10.18502/jhsw.v15i1.21363

Aida Naghshbandi Department of Occupational Health Engineering, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Omran Ahmadi Department of Occupational Health Engineering, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

DOI: https://doi.org/10.18502/jhsw.v15i1.21363

Keywords: Bayesian network, Excavation, Fuzzy DEMATEL, Gas pipelines, Piping operation

Abstract

Introduction: Identifying and modeling the root causes of accidents can play an important role inpreventing them. The purpose of this study is to identify and model the causes of gas pipeline excavationand piping operation accidents using the Bayesian network (BN) and fuzzy DEMATEL.

Material and Methods: In this study, industrial accidents during gas pipeline excavation and pipingoperations were analyzed using the Bowtie method. The fuzzy DEMATEL method was employed todetermine relationships between accident root causes, and the fuzzy AHP method was used to comparepairs of causes and determine their weight. Finally, Bowtie and DEMATEL outputs were mapped inBayesian networks to determine the important risk factors for accidents.

Results: The most important risk factors for trench collapse accidents were as follows: risk management(16% impact weight), competency assessment (14.2% impact weight), supervision (13.8% impact weight),work permit system (13.7% impact weight), compliance with requirements and guidelines (13.4% impactweight), training (11.4% impact weight), HSE system (9.5% impact weight), and contractor management(8% impact weight).

Conclusion: Based on the results, it was demonstrated that risk management and competency assessment,having the highest weight percentages, play the most significant roles in the occurrence of trench collapseaccidents. The findings of this study can inform the prioritization of corrective measures to prevent trenchcollapse accidents in gas pipeline excavation and piping operations.