Application of the Taguchi Method to Optimize the Process Parameters of a Single-slope Solar Still Integrated with a Solar Pond

This study employs the Taguchi optimization method to enhance the performance of a single-slope solar still (SSSS) integrated with a solar pond. Key variables, including solar radiation (600 to 1000 W/m²), water depth (4 to 8 cm), inlet water temperature (30 to 40 °C), and wind speed (1 to 5 m/s), were tested using an L9 orthogonal array. Signal-to-noise ratio analysis was used to identify optimal settings, while analysis of variance determined the most significant factors. Regression analysis established the relationship between input parameters and system outputs, including freshwater yield and basin water temperature. The highest productivity was achieved under conditions of 1000 W/m² solar radiation, a 4 cm water depth, a 3 m/s wind velocity, and a 40 °C inlet temperature. Under optimized conditions, the solar still exhibited a predicted productivity of 1.131 kg/m², with an experimental deviation of 9.31%. The basin water temperature showed a minimal deviation of 2.18%. These results technically confirm the robustness of the regression models and the reliability of the optimized process parameters. The strong agreement between predicted and observed values confirms the reliability of the model and the effectiveness of the optimization strategy in improving the solar still performance.