Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil–water mixture (POME model) using the progressive freezing process was investigated. An optimization technique called response surface methodology (RSM) with the design of rotatable central composite design was applied to figure out the optimum experimental variables generated by Design–Expert software (version 6.0.4. Stat-Ease, trial version). Besides, RSM also helps to investigate the interactive effects among the independent variables compared to one factor at a time. The variables involved are coolant temperature, X_A (4–12 °C), freezing time, X_B (20–60 min), and circulation flow, X_C (200–600 rpm). The statistical analysis showed that a two-factor interaction model was developed using the obtained experimental data with a coefficient of determination (R²) value of 0.9582. From the RSM-generated model, the optimum conditions for extraction of oil from the POME model were a coolant temperature of 6 °C in 50 min freezing time with a circulation flowrate of 500 rpm. The validation of the model showed that the predicted oil yield and experimental oil yield were 92.56 and 93.20%, respectively.

中文翻译：

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从棕榈油-水混合物中进行剩余油采收的渐进冷冻优化（POME模型）

尽管对POME进行了常规处理，但油脂仍然是棕榈油厂废水（POME）中的主要污染物。研究了使用渐进冷冻方法从棕榈油-水混合物（POME模型）中去除残留油的方法。采用可旋转中央复合材料设计的一种称为响应面方法（RSM）的优化技术，以找出由Design-Expert软件（版本6.0.4。Stat-Ease，试用版）生成的最佳实验变量。此外，RSM还有助于一次调查与一个因素相比的自变量之间的交互作用。涉及的变量是冷却液温度X _A（4–12°C），冻结时间，X _B（20–60分钟）和循环流量，X _C（200–600 rpm）。统计分析表明，使用获得的实验数据建立了两因素相互作用模型，测定系数（R ²）值为0.9582。从RSM生成的模型中，从POME模型中提取油的最佳条件是在50分钟的冷冻时间内冷却液温度为6°C，循环流量为500 rpm。模型的验证表明，预测的油产率和实验油产率分别为92.56％和93.20％。