An Adaptive Slicing Thickness Adjustment Method Based on Cloud Point in 3D Printing

This paper introduces an approach for slicing thickness adaptively based on cloud point that aims at the problem of a large amount of data, inefficiency and low precision of 3D printing. The proposed method can select the optimum slicing thickness adaptively based on error analysis of point cloud belt in unified slicing direction by adopting the optimizing quadtree structure of point cloud to store point cloud data. In view of the different complexity model to evaluate the experiment. The result demonstrates that the computational complexity of proposed method decreased by 30% compared with method II. It is suitable for elaborate model of layered manufacturing printing.