A Graphical Approach for Freeform Surface Offsetting With GPU Acceleration for Subtractive 3D Printing

Abstract

The lack of plug-and-play programmability in conventional toolpath planning approach in subtractive manufacturing, i.e., machining leads to significantly higher manufacturing cost for CNC based prototyping. In computer aided manufacturing (CAM) packages, typical B-rep or NURBS based representations of the CAD interfaces challenge core computations of tool trajectories generation process, such as, surface offsetting to be completely automated. In this work, the problem of efficient generation of free-form surface offsets is addressed with a novel volumetric representation. It presents an image filter based offsetting algorithm, which leverages the parallel computing engines on modern graphics processor unit (GPU). The scalable voxel data structure and the proposed hardware-accelerated volumetric offsetting together advance the computation and memory efficiencies well beyond the capability of past studies. Additionally, in order to further accelerate the offset computation the problem of offsetting with a large distance is decomposed into successive offsetting using smaller distances. The accuracy of the offset algorithms is thoroughly analyzed. The developed GPU implementation of the offsetting algorithm is robust in computation, easy to comprehend, and achieves a 50-fold speedup on single graphics card (NVIDIA GTX780Ti) relative to prior best-performing dual socket quad-core CPU implementation.