Predictive Model of Surface Roughness in Active Fluid Jet Polishing of Optical Components

ABSTRACT

Because of its high convergence rate for high‐frequency errors and conforming polishing capability, active fluid jet polishing (A‐FJP) has become a vital technology for the processing of optical components. The quality of optical components is usually evaluated by surface roughness (SR), directly influencing their optical performance and practical application effectiveness. For an in‐depth understanding of the A‐FJP process and its impact on SR, a prediction model is proposed in this study to evaluate the SR of optical components. First, the motion path of individual abrasives and the velocity distribution of the pad were modeled. Subsequently, a pressure distribution model was developed through fluid–structure interaction simulation. The material removal volume (MRV) per single abrasive and the number of effective abrasives were calculated. Models for both macroscale and microscale MRV were constructed separately. Ultimately, an A‐FJP roughness prediction model considering multiple process parameters was proposed. This model was validated through orthogonal process experiments. The results indicate that the maximum prediction error is 9.31%. An orthogonal experiment was conducted; through the analysis of variance, it was found that under the optimal process parameters, the SR decreased by 54.74% compared to the minimum value before optimization. The influence order of process parameters on SR is as follows: jet pressure > polishing time > spindle speed. These results verify the accuracy of the model and provide practical guidance for effectively controlling SR in A‐FJP.