Abstract
A novel surface adaptive polishing (SAP) process is initially proposed to efficiently improve the surface accuracy of optical freeform surfaces while suppressing their surface and subsurface damage. A multiscale theoretical model is developed to predict the generation of surface microtopography. This model captures considerable fundamental physics of the SAP process, such as the variable curvature characteristics of the workpiece surface, the surface topography of pad, the brittle-ductile removal effect of materials, and the trochoidal motion trajectories of polishing tool. The feasibility and accuracy of the model were quantitatively analyzed through a series of experiments. Moreover, the influence mechanism of process parameters on surface morphology and subsurface damage was studied. The simulated results by the theoretical model agree well with the experimental data, and maximum relative errors of material removal rate (MRR) and surface roughness Sa are 3.91 % and 1.38 %, respectively. Results indicated that the SAP process can produce axisymmetric Gaussian removal functions, significantly remove the damage layer, and improve the surface quality while avoiding the generation of periodic surface textures. The increase in the tool offset changes the material removal mode from ductile to brittle mode, resulting in a higher MRR and Sa. In addition, the Taguchi simulation experiments are conducted to quantitatively evaluate the significance of the process parameters.
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