Ahmad Barari PhD, PE, Assistant Professor, University of Ontario Institute of Technology
Hossein Gohari, PhD Student, University of Ontario Institute of Technology (UOIT)
Modeling, analysis and construction of a virtual part in digital manufacturing is commonly conducted by employing parametric surfaces. However, in order to slice a geometry for 3D printing, the common practice is to use the triangular tessellation of the exact parametric surfaces. This practice potentially causes inaccuracies in the additive manufacturing processes. The current research is focused on direct slicing of the parametric surfaces to avoid issue of any tessellation error into fabrication. In this work, the slicing parameters of fabrication layers are extracted based on the parameterization of the geometric surface defining the workpiece. The parameterization is proposed by combination of the Milne-Simpson multistep method and a function of curvature. The main goal is to analytically find cross sections of a parametric surface regarding the desired geometrical characteristics. The desired geometrical characteristics can be classified based on area, surface signature and curvature attitudes, and can be directly used for precision Additive Manufacturing. To achieve the desired level of accuracy, the curvature is found to be a suitable characteristic to guide slicing a parametric surface.