CONTACT US: Contact info
|
Citation |
Ebrahimi H, Zarei E, Ansari M, Nojoumi A, Yarahmadi R. Safety Sci. 2024; 173: e106445. |
|
Copyright |
(Copyright © 2024, Elsevier Publishing) |
|
DOI |
|
PMID |
unavailable |
|
Abstract |
This paper presents a novel framework that combines the Systems-Theoretic Accident Model and Processes (STAMP) with Decision Making Trial and Evaluation Laboratory (DEMATEL) and Fuzzy logic to achieve a quantitative non-linear accident analysis methodology. The proposed methodology consists of two primary stages. Firstly, a qualitative analysis of a fatal accident is conducted using STAMP. The accident's control structure is constructed, and unsafe control actions (UCAs) are pinpointed. Secondly, the Fuzzy-DEMATEL approach is employed to quantify and determine the relationships between different control levels. A diverse pool of experts' opinions is leveraged to assess the impact of each control level on others and accident scenarios. The findings reveal that various interactions between Operation, HSE, Business, Contracting, Firefighting, and Management levels contributed to the occurrence of the accidents. The integrated approach not only addressed qualitative nature of STAMP, but also elucidates the cause-effect relationships among control levels. The significance of this study lies in its ability to not only analyze past accidents but also proactively examine the system and identify hazardous control levels before accidents occur. By prioritizing control levels and understanding their interconnections, organizations can implement targeted safety measures to prevent accidents and enhance overall system reliability and resilience. Its effectiveness in quantifying data, identifying unsafe control actions, and establishing cause-effect relationships make it a valuable tool for enhancing safety in various complex socio-technical systems beyond the process industry. Language: en |
|
Keywords |
Causality analysis; Causation models; Chemical process industry; Multi-disciplinary analysis; Operational interdependencies |