Abstract
This paper presents an efficient method for computing machined part geometry and cutter-workpiece engagement in general multi-axis milling. The milling process in this work is simulated by multi-level voxel update and edge intersection point update in sub-voxel level. The computed intersection points are used not only for building the machined part mesh model via dynamic marching cubes algorithm, but also for determining the instantaneous cutter-workpiece engagement region. The multi-level representation of the workpiece enables batch processing of affected voxels and minimal intersection calculations for more rapid and accurate modeling results. Virtual prototyping of the milled part geometry is critical for tool path planning, while cutter-workpiece engagement is one of the most important inputs for cutting force prediction. In a series of test cases, the proposed method has shown satisfactory modeling accuracy and higher efficiency compared to the tri-dexel model. More importantly, this volumetric method is implemented on six different data structures which are obtained by combining the fundamental spatial decomposition strategies. The efficiency characteristics of the resulting data structures are studied quantitatively which will help select the most appropriate scheme according to the performance requirements and realize its full potential for improved efficiency by choosing the optimal branching factors.