To improve surface roughness of components without altering geometrical dimensions, polishing operations are commonly used. These operations may be time-consuming and expensive. Thus, the prediction of polished surface quality is a key issue to reduce the cost of these operations. Resulting surface quality of polishing operations is the outcome of a large number of local cutting phenomena (grains-material). The control of the multi-scale physical phenomena is a challenge when it comes to simulate these operations. In this paper, an Analytical-Method for Polishing-Surface Prediction (AMPSP) that considers the tool flexibility and each grain-material interaction is proposed. The objective is to predict accurately the polished surface topography and the material removal rate, and to keep the history of all the local cutting phenomena, in order to define a digital twin of polishing operation. Experimental validation demonstrates that this AMPSP predicts the material removal rate (less than 35% of error) and the surface topology (less than a few percent). AMPSP will enable engineers to quickly and accurately predict the polished topology obtained with 5-axis toolpaths.

为了在不改变几何尺寸的情况下提高部件的表面粗糙度，通常使用抛光操作。这些操作可能是耗时且昂贵的。因此，抛光表面质量的预测是降低这些操作成本的关键问题。抛光操作产生的表面质量是大量局部切割现象（晶粒材料）的结果。模拟这些操作时，多尺度物理现象的控制是一个挑战。在本文中，提出了一种考虑工具灵活性和每种晶粒-材料相互作用的抛光表面预测的分析方法（AMPSP）。目的是准确预测抛光表面的形貌和材料去除率，并保留所有局部切削现象的历史记录，为了定义抛光操作的数字孪生。实验验证表明，该AMPSP可以预测材料的去除率（误差小于35％）和表面拓扑结构（小于百分之几）。AMPSP将使工程师能够快速准确地预测使用5轴刀具路径获得的抛光拓扑。