Abstract

In this study, we propose a tool-path generation approach for material extrusion-based additive manufacturing (AM) that considers the machining efficiency and fabrication precision, which are inherent drawbacks of general AM techniques compared with conventional manufacturing methods. The proposed approach aims to tackle the generation of direction-parallel tool-paths for the interior filling of simple connected areas, which comprises three main steps: (1) determining the inclination of reference lines; (2) generating and grouping tool-path segments into individual sub-paths; and (3) linking sub-paths based on specific requirements. These three modules interact to affect the efficiency and precision of AM significantly. In order to find an optimal inclination, we first analyze the impacts on the fabrication efficiency and manufacturing accuracy with different inclinations. A comparatively accurate building time model is developed subsequently to obtain the optimal tool-path inclination, but without compromising the machining precision, based on the analysis of a geometrical accuracy model. The proposed approach employs different inclinations in distinct layers according to specific manufacturing scenarios and technological requirements. After determining the reference lines, the tool-path segments are selected and grouped based on some characteristics (e.g., the number of intersections between reference lines and boundaries) to make up individual sub-paths, which are then connected to a zigzag-shaped path with short line segment connections. In the module for sub-path linking, some strategies are introduced to decrease the number of useless tool-paths, i.e., uncut paths, which could jeopardize the manufacturing quality by frequently turning the print head on and off. In addition, parametric curves are used to link the final sub-paths to avoid deceleration/acceleration processes in the end/starting parts of the sub-paths. The proposed approach has been used in practice to generate tool-paths for a wide range of models and the results verify its effectiveness and obvious advantages.

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