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Purpose Material extrusion (ME) suffers from anisotropic mechanical properties that stem from the three degree of freedom (DoF) toolpaths used for deposition. The formation of each layer is restricted to the XY-plane, which produces poorly bonded layer interfaces along the build direction. Multi-axis ME affords the opportunity to change the layering and deposition directions locally throughout a part, which could improve a part’s overall mechanical performance. The purpose of this paper is to evaluate the effects of changing the layering and deposition directions on the tensile mechanical properties of parts printed via multi-axis ME. Design/methodology/approach A multi-axis toolpath generation algorithm is presented and implemented on a 6-DoF robotic arm ME system to fabricate tensile specimens at different global orientations. Specifically, acrylonitrile butadiene styrene (ABS) tensile specimens are printed at various inclination angles using the multi-axis technique; the resulting tensile strengths of the multi-axis specimens are compared to similarly oriented specimens printed using a traditional 3-DoF method. Findings The multi-axis specimens had similar performances regardless of orientation and were equivalent to the 3-DoF specimens printed in the XYZ orientation (i.e. flat on the bed with roads aligned to the loading condition). This similarity is attributed to those sets of specimens having the same degree of road alignment. Practical implications Parts with out-of-plane loads currently require design compromises (e.g. additional material in critical areas). Multi-axis deposition strategies could enable local changes in layering and deposition directions to more optimally orient roads in critical areas of the part. Originality/value Though multi-axis ME systems have been demonstrated in literature, no prior work has been done to determine the effects of the deposition angle on the resulting mechanical properties. This work demonstrates that identical mechanical properties can be obtained irrespective of the build direction through multi-axis deposition. For ABS, the yield tensile strength of vertically oriented tensile bars was improved by 153 per cent using multi-axis deposition as compared to geometrically similar samples fabricated via 3-DoF deposition.

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The layer-by-layer deposition process used in material extrusion (ME) additive manufacturing results in inter- and intra-layer bonds that reduce mechanical performance. Multi-axis ME techniques have shown potential for mitigating this issue by enabling tailored deposition directions based on loading conditions in three dimensions (3D). Planning deposition paths leveraging this capability remains a challenge, as an intelligent method for assigning these directions does not exist. Existing literature introduced topology optimization (TO) methods that assign material orientations to discrete regions of a part by simultaneously optimizing material distribution and orientation. These methods are insufficient for multi-axis ME, as the process offers additional freedom in varying material orientation that is not available to those methods. Additionally, optimizing orientation design spaces is difficult, and this issue is amplified with increased flexibility; the chosen orientation parameterization heavily impacts the algorithm's performance. Therefore, the authors i) present a TO method to solve the simultaneous problem with considerations for 3D material orientation variation and ii) establish a suitable parameterization of the orientation design space. Three parameterizations are explored in this work: Euler angles, explicit quaternions, and natural quaternions. The parameterizations are compared using two benchmark minimum compliance problems: a 2.5D Messerschimitt-Böolkow-Blohm beam and a 3D Wheel. For the Wheel, the presented algorithm demonstrated a 38% improvement in compliance over an algorithm that only allowed planar orientation variation. Additionally, natural quaternions maintain the well-shaped design space of explicit quaternions without unit length constraints, which lowers computational costs.