Optimization of Process Parameters for Electrostatic Rotary Bell Spraying Based on Response Surface Methodology

The electrostatic rotary bell (ESRB) sprayer is widely used in the coating industry due to its ability to achieve uniform film thickness and reasonable paint transfer efficiency. However the efficiency of paint transfer and spraying coverage in ESRB systems remain highly sensitive to process parameters. Therefore, optimizing these parameters is essential to reducing paint consumption, energy use, and environmental impact. In this study, a simulation model of the ESRB spraying process was established using ANSYS/Fluent. The spraying flow field, paint deposition profile, and film thickness distribution were validated through the experiment. Based on a single-factor test and the Box–Behnken response surface method, a multi-parameter optimization framework was designed to investigate the effects of six spraying process parameters, including inner and outer shaping air flow rate, bell rotational speed, applied voltage, target distance, and paint flow rate, on coating pattern width and paint transfer efficiency. Based on the Z-score standardization, a mathematical model of the comprehensive score with six factors was established to evaluate spraying efficiency and paint transfer efficiency and predict optimal spraying process parameters. The results indicate that voltage and spray distance are significant factors affecting the comprehensive score, with the order of influence being voltage > spray distance. The optimal parameters were as follows: bell rotational speed X1, 40 kr/min; inner shaping air flow rate X2, 196 sl/min; outer shaping air flow rate X3, 298 sl/min; paint flow rate X4, 249 cc/min; applied voltage X5, 52 kV; and target distance X6, 154 mm. Validation tests showed deviation between the predicted comprehensive score and the actual value from simulation and experiment were 2.03% and 1.36%, respectively. These results demonstrate that the proposed optimization model has high reliability and can be used to optimize spraying process parameters.