William Oropallo

I developed an algorithm that generates point clouds and slices models within a tolerance. The algorithm uses the original NURBS model and converts the model into a point cloud, based on layer thickness and accuracy requirements. The algorithm then uses a gridding structure to calculate where intersections happen and fit B-spline curves to those intersections. This dissertation shows that a point cloud approach to preprocessing and slicing models is robust and accurate. This method can find accurate intersections and can ignore certain anomalies and errors from the modeling process. The point cloud approach to object slicing avoids the complexities of directly slicing models while evading the error-prone tessellation stage.

After researching and synthesizing the current literature in the domain of 3D printing, I wrote this piece to summarize the most pressing difficulties in the field. The purpose of this paper is to paint a more realistic picture by identifying ten challenges that clearly illustrate the limitations of the technology. Others have cited this paper in over 140 other works as of March 2020.