A novel 3D surface topography prediction algorithm for complex ruled surface milling and partition process optimization

Abstract

The ruled surface is an important modeling method of the product. With high-performance requirement, more and more complex ruled surfaces with the characteristic of variant curvature are used in auto, aviation, or die mold. The time-varying tool position and orientation make the prediction of surface topography very difficult in the five-axis machine tool processing. In this paper, a three-dimensional surface topography prediction method is proposed. The point cloud of cutting edge is obtained after a series of matrix transformation by calculating the instant information of the local tool coordinate. Then, lots of tiny bounding boxes are constructed based on the profile of the workpiece. The 3D surface topography is obtained by the Boolean operation between the enveloping body of cutting edge and the tiny bounding boxes. The geometric error of the machine tool, the vibrations, and the deformation of the tool is also considered in the generation of the surface topography. The presented method is validated by a case study of the S test piece. The prediction results are verified by the measuring experiment at the same time. Finally, a partition optimization method on the surface topography for the complex surface of the S test piece is presented. The dynamic modification of the cutting parameters in different partitions of the milling process can greatly improve the surface quality without reducing efficiency.