Recommended slicing positions for adaptive direct slicing by image processing technique

Abstract

Build time and accuracy are two contradicting issues that have been a major concern in rapid prototyping, and have led to the development of many slicing approaches including those applying adaptive slicing, direct slicing, and adaptive direct slicing concepts. Presented in this paper is an approach for adaptive direct slicing that applies image processing technique to determine appropriate thickness for each sliced layer and to recommend slicing positions on a 3D CAD model. Two orthogonal views of a model are captured and converted to be edge images before being analyzed, and based on the surface complexity on the two edge images, slicing positions are recommended. These positions are passed to the CAD software for slicing activities. This adaptive direct slicing approach has been implemented on LabVIEW platform and compared with uniform direct slicing approach and uniform cusp height approach. The results show that this slicing approach improved slicing performance by reducing the number of layer which has a direct impact on build time while maintaining surface quality at the same level as the thin uniform direct slicing. Since its inputs are the images of a CAD model instead of the model itself, this adaptive direct slicing supports any CAD software.