This work proposes an innovative statistical model by utilizing the response surface methodology (RSM) method to analyze a batch solar behaviour still. This investigation's main goal is to study the impact of the input factors (solar radiation, ambient temperature, water depth, and thickness of insulation) most influencing water productivity. The polynomial regression model derived from a numerical balance energy model to predict the solar's productivity still is established. The quadratic model is checked by a coefficient of determination (R²). An excellent fitting is attained between the forecasted results derived from the statistical model and the numerical simulation derived from the heat balance model. The results reveal that the importance of the influence in the order of impact on the amount of distilled water is water depth, solar radiation, ambient temperature, and thickness of insulation. A simple polynomial statistical model is stated in this investigation to determine and maximize the amount of distilled water from solar still based on the four considered input factors.

这项工作通过利用响应面方法（RSM）方法来分析批次太阳行为仍然提出了一个创新的统计模型。这项调查的主要目标是研究最影响水生产率的输入因素（太阳辐射，环境温度，水深和绝缘厚度）的影响。建立了从数值平衡能量模型推导来预测太阳能生产率的多项式回归模型。通过确定系数检查二次模型（R ²）。从统计模型得出的预测结果与从热平衡模型得出的数值模拟之间达到了极好的拟合。结果表明，影响顺序对蒸馏水量的影响的重要性在于水深，太阳辐射，环境温度和绝缘层厚度。在这项研究中提出了一个简单的多项式统计模型，用于基于四个考虑的输入因素来确定和最大化来自太阳能蒸馏器的蒸馏水量。