The study titled Enhancing HFO Separator Efficiency: A Data-Driven Approach to Petroleum Systems Optimization investigated the quantitative relationships between thermophysical, mechanical, and operational parameters that determine the performance efficiency of heavy fuel oil (HFO) centrifugal separators. Using a data-driven framework, the research analyzed empirical field data supported by an extensive review of 112 scholarly and industrial studies focusing on petroleum separation technologies, machine learning applications in process optimization, and reliability-based maintenance modeling. The quantitative methodology incorporated multiple regression and mixed-effects models to evaluate the influence of inlet temperature, viscosity, flow rate, bowl rotational speed, torque, and vibration amplitude on overall separator efficiency, measured through a composite Efficiency Index (EI) integrating residual water, solids concentration, and energy consumption per ton of fuel treated. The findings revealed that inlet temperature had a significant positive impact on separator efficiency, whereas viscosity, torque, and vibration amplitude exhibited strong negative effects. Bowl rotational
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