Fuzzy cognitive mapping-driven knowledge management based on 24Model for major accident prevention: a case study of oil and gas industry
Wafa Boulagouas
What the paper says
The oil and gas industry is prone to major hazard accidents, often triggered by human error and systemic failures. This study introduces a novel approach to major accident prevention through the development of a fuzzy cognitive mapping (FCM)-driven knowledge management (KM) framework based on the 24Model. The study aims to: 1) map critical accident causative factors using the 24Model; 2) develop and validate a KM framework integrating FCM for simulation-based analysis; 3) apply this framework to a real-world case in the oil and gas sector. The FCM-driven KM framework provides a systematic approach for identifying and analysing accident factors, offering decision-makers actionable insights to improve risk management, maintenance practices, and safety culture. Theoretically, this research extends existing models by integrating the 24Model with FCM. From a policy perspective, the study emphasises the importance of stricter regulations and enforcement to support a strong safety culture and reduce the likelihood of major accidents.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.