Resilience evaluation of prefractionation section (SBAA refinery) integrating FRAM & BN

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dc.contributor.authorNEDJAR Yassine, MIDOUNI Khalil, ABBOU Abderrahmane Enc: BOUAFIA Abderraouf, BOUGOFA Mohammed
dc.date.accessioned2026-01-11T09:13:37Z
dc.date.available2026-01-11T09:13:37Z
dc.date.issued2023-07-11
dc.description.abstractThis dissertation aims to evaluate the resilience of the pre-fractionation section in the Adrar Sbaa refinery by integrating the Functional Resonance Analysis Method (FRAM) and Bayesian Networks (BN). FRAM provides a comprehensive understanding of system functions, variability, and interdependencies, while the BN offers a probabilistic framework for capturing dependencies and making inferences. The research focuses on developing a FRAM model and then converting it to a Bayesian Network model to quantify the resilience of system reliability. The methodology includes data collection, analysis, and synthesis, with a sensitivity analysis to assess the models' robustness. The integrated approach allows for a holistic assessment of the section's adaptive capabilities and recovery potential, facilitating informed decision-making and resilience planning.
dc.identifier.urihttp://dspace.univ-skikda.dz:4000/handle/123456789/5697
dc.language.isoen
dc.publisher20 AUGUST 1955 SKIKDA UNIVERSITY: FACULTY OF TECHNOLOGY (DEPARTMENT PROCESS ENGINEERING)
dc.titleResilience evaluation of prefractionation section (SBAA refinery) integrating FRAM & BN
dc.title.alternativeIndustrial Hygiene and Safety
dc.typeThesis
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