A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling

A Framework for Adaptive Width Control of Dense Contour-Parallel Toolpaths in Fused Deposition Modeling

Kuipers, T. (TU Delft Materials and Manufacturing; Ultimaker)
Doubrovski, E.L. (TU Delft Mechatronic Design)
Wu, J. (TU Delft Materials and Manufacturing)
Wang, C.C. (The Chinese University of Hong Kong)

2020

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. Objects are produced by filling (a portion of) the 2D polygons of consecutive layers with contour-parallel extrusion toolpaths. Uniform width toolpaths consisting of inward offsets from the outline polygons produce over- and underfill regions in the center of the shape, which are especially detrimental to the mechanical performance of thin parts. In order to fill shapes with arbitrary diameter densely the toolpaths require adaptive width. Existing approaches for generating toolpaths with adaptive width result in a large variation in widths, which for some hardware systems is difficult to realize accurately. In this paper we present a framework which supports multiple schemes to generate toolpaths with adaptive width, by employing a function to decide the number of beads and their widths. Furthermore, we propose a novel scheme which reduces extreme bead widths, while limiting the number of altered toolpaths. We statistically validate the effectiveness of our framework and this novel scheme on a data set of representative 3D models, and physically validate it by developing a technique, called back pressure compensation, for off-the-shelf FDM systems to effectively realize adaptive width.

Adaptive extrusion width
Additive manufacturing
Geometrical accuracy
Medial axis transform
Toolpath generation

http://resolver.tudelft.nl/uuid:202cfa0a-4c59-415d-beba-6bc7d16568b9

https://doi.org/10.1016/j.cad.2020.102907

0010-4485

Computer-Aided Design, 128, 1-15

Institutional Repository

journal article

© 2020 T. Kuipers, E.L. Doubrovski, J. Wu, C.C. Wang