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

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Date
2023-07-11
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20 AUGUST 1955 SKIKDA UNIVERSITY: FACULTY OF TECHNOLOGY (DEPARTMENT PROCESS ENGINEERING)
Abstract
This 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.
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