Fig. 1. A general workflow of 3D printing preprocessing
Fig. 2. Number of publications on multiaxis 3D printing
[20] Fig. 3. Non-uniform slicing method
[30] Fig. 4. Unit layer slicing method
[31]. (a) Unit layer;(b) result of slicing; (c) unit layer after deposition
Fig. 5. Offset slicing method
[32]. (a) Base surface of contour; (b) offset slices obtained from base surface
Fig. 6. An illustration of method proposed by Lee and Jee
[33]. (a) STL model; (b) overhang/overcutting identification;(c) overhang/overcutting volume decomposition; (d)(e) slicing in multiple directions
Fig. 7. Illustration of decomposition-regrouping method
[34]. (a) Sub-volumes, feature regions (red), and base region;(b) grouped sub-volumes; (c) slicing in multiple directions
Fig. 8. Cylindrical coordinate slicing method
[35]. (a) Revolving part; (b) cylindrical coordinate; (c) intersection contour of slice with overhang structure; (d) mapped overhanging structure at Cartesian coordinate
Fig. 9. Nonplanar slicing method proposed by Zhao et al
[36]. (a) Decomposed volumes; (b) offset surfaces; (c) trimmed surfaces; (d) five-axis toolpaths
Fig. 10. Non-uniform slicing method based on centroidal axis
[37]. (a) Solid model; (b) centroidal axis; (c) centroidal axis and solid model; (d) decomposed result; (e) slicing result
Fig. 11. Illustration of method proposed by Wang et al
[40]. (a) Input Y shape model; (b) three extracted skeletal polylines of
,
, and
; (c) coarse segmentation result based on skeletons from Fig. 11(b) by evaluating shape diameter; (d) find the risky facets of model surface under a variable printing direction; (e) partition the model into two printable parts A
* and B
* with a partition plane; (f) skeleton
, as part of
, is reserved B
* after plane clipping, and a single skeleton
is re-extracted from trunk model A
*; (g) C, E, and G printed in fixed directions; (h) final decomposition result
Fig. 12. Model decomposition method proposed by Wu et al
[41]. (a) Input 3D model; (b) extracted skeleton; (c) distribution of shape diameter metric; (d) initial decomposition and print order results; (e) result after merging (B+A); (f) final result after fine decomposition (meet manufacturability requirements)
Fig. 13. Volume decomposition algorithm proposed by Dai et al
[48]. (a) Input 3D model; (b) voxel discretization and accumulative voxel sequence; (c) generating curved layers based on Fig. 13(b); (d) a detailed view on a computed toolpath
Fig. 14. Volume decomposition algorithm proposed by Xu et al
[51]. (a) Original mesh model; (b) generated iso-geodesic contours; (c) reconstructed surface layers with no intersection
Fig. 15. Volume decomposition algorithm proposed by Fang et al
[55]. (a) A bunny-head model H is represented by a tetrahedral mesh
T; (b) principal stresses with values are visualized by colors; (c) a vector-field
V(
x) is optimized according to the principle of reinforcement and the fabrication constraints; (d) a scalar-field
G(
x) is obtained by enforcing ∇
G(
x) to follow
V(
x); (e) preliminary curved layers are generated by extracting the iso-surfaces from
G(
x); (f) an orientation of fabrication is determined by considering the accessibility of printer head and regions with large overhangs are detected by a sampling based method; (g) a vector-field
V(
x) is extrapolating
V(
x) for supporting structure; (h) final curved layers are extracted from the governing fields for 3D printing; (i) toolpaths are generated for curved layers according to the principal stresses
Fig. 16. Illustrate of ellipsoid based curved slicing
[57]. (a) A characteristic ellipsoid of a sub-entity; (b) intermediate ellipsoid generation
Fig. 17. Schematic of the method proposed by Kapil et al
[59]. (a) Position of cladding torch and substrate; (b) tilted substrate for 5-axis outer contour deposition; (c) vertical substrate for 2.5 axis area filling
Fig. 18. Horizontal planes with equal distances
h between each other generate different layer thicknesses in the welding direction
[61] Fig. 19. A novel deposition strategy for creating overhangs proposed by Dai et al
[62-63]. (a) A common strategy of depositing filling paths layer by layer; (b) a novel strategy of depositing the overhanging segment as a support; (c) deposition of filling paths
Fig. 20. Illustrate of staircase effect under three conditions
[23]. (a)
P⊆
Q; (b)
Q⊆
P; (c)
P⊄
Q Fig. 21. Comparison of methods between planar slicing and slightly curved slicing
[68]. (a) Planner slicing method; (b) slightly curved slicing method
Fig. 22. Helical slicing method
[69]. (a) Model input; (b) generate slicing planes; (c) obtain planar slices; (d) generate direction vectors; (e) generate helical points; (e) generate helical toolpath
Fig. 23. Slicing and path generation method and actual print results for RotBot
[81] Fig. 24. Singularity aware motion planning
[93]. (a) Singularity aware optimization is not used; (b) singularity aware optimization is used
Original input model | Decomposed result by Wu et al[41] | Decomposed result by Xu et al[45] | Decomposed result by Xiao et al[46] |
---|
| | | | | | Cannot be processed | | | | Cannot be processed | |
|
Table 1. Comparison of decomposition results based on constrained optimization methods
[46] Ref. | Year | Category | Suitable type of models | Decomposing with planes or surfaces | Limitation | Platform type | DOF |
---|
Dep.head | Build plate |
---|
[41] | 2017 | Shape-analysis-based decomposition, constrained fine tuning | Multi-branched structure; volumes with non-shape edges | Planes | Root node of print sequence needs to be manually intervention | 6-DOF robotic arm | 0 | 3 trans., 3 orient. | [42] | 2019 | Constrained optimization, heuristic search(ant colony algorithm) | Volumes with non-shape edges; ring-like models(compared with results of Ref. [41]) | Planes | Number of cutting planes need to be manually intervention; not efficient | 5-axis CNC machine | 3 trans. | 2 orient. | [44] | 2019 | Constrained optimization, gravity-effect partition | Overhanging features with sharp concave edges or concave loops | Planes | Several type of workpieces like hollow cubic cannot be partitioned | 5-axis CNC machine | 3 trans. | 2 orient. | [45] | 2019 | Constrained optimization, downward flooding search | Tree structure | Planes | Sub-volumes which may interference with printing nozzle should be merged manually | 3 -axis(tested their method by assembly parts), | - | - | [43] | 2020 | Constrained optimization, beam-guided search | Volumes with non-shape edges (compared with results of Ref. [45]) | Planes | Rotational axis should be chosen carefully | 6-DOF robotic arm | 0 | 3 trans., 3 orient. | [46] | 2020 | Constrained optimization | Overhanging features with sharp concave edges or concave loops; ring-like models; volumes with non-shape edges | Planes/surfaces | Rotational axis should be chosen carefully | 3 -axis (tested their method by assembly parts) | - | - |
|
Table 2. Comparison of characteristics of constraint-based optimization methods
Ref. | Year | Category | Suitable type of models | Limitation | Platform type | DOF |
---|
Generation method of initial curved layers | Generation method of curved toolpath | Classification of curved toolpath | Optimization method of orientation-smoothing | Dep. head | Build plate |
---|
[47] | 2018 | Growing field generated by determining an order of voxel accumulation | Generated by FWP-MMP method | Continuous fermal spiral tool-path | Low pass filtering sampling; quaternion interpolation | Volumes with non-shape edges | Discretization error; Not efficient; Lower surfaces quality | 6-DOF robotic arm | 0 | 3 trans., 3 orient. | [51] | 2019 | Scalar field computed based on MMP algorithm | Geodesic distance field computed based on MMP method | Contour-parallel path | 5-point sampling with Gaussian hemisphere interpolation | Volumes with non-shape edges | Potential local interference; low productivity | 6-DOF robotic arm | 0 | 3 trans., 3 orient. | [53] | 2020 | Geodesic distance field based on heat method | Geodesic distance field based on heat method | Contour-parallel path | - | Multi-branched structure | Parts with complicated topologies may lead to collision | 5-axis printing system | 3 trans. | 3 trans., 3 orient. | [55] | 2020 | Scalar-field according to stress analysis(based on Abaqus) | Scalar-field according to stress analysis(based on Abaqus) | Hybrid strategy(contour-parallel path and directional- parallel path) | - | Volumes with non-shape edges | Supports needed; low productivity | 5-axis CNC machine | 3 trans. | 2 orient. | [56] | 2021 | Temperature field based on COMSOL | Based on heat method | Contour-parallel path | - | Overhanging features are sharp concave edges or concave loops | Potential local interference; not efficient | 5-axis printing system | 3 trans. | 2 orient. | [57] | 2022 | Ellipsoidal slicing | Field based method | Contour-parallel path(iso-cusp height printing path) | - | Volumes with non-shape edges | Complex algorithms; global interference is not considered | 5-axis printing system | 3 trans. | 3 trans., 3 orient. | [58] | 2021 | - | - | - | - | Thin-walled structure | Affected by human experience | 6-DOF robotic arm | 0 | 3 trans., 3 orient. |
|
Table 3. Summary and comparison of methods based on curved layer decomposition
Method | Category | Suitable type of models | Characteristic | Impact of manufacturing process | Main application |
---|
Overhang structure decomposition | Planner multi-axis | Overhanging features are sharp concave edges or concave loops | Easy to control; efficient | Alleviated anisotropy; high surface quality | FDM, WAAM, LDMD | Skeletonization | Planner multi-axis; nonuniform | Multi-branched or tree structure | Easy algorithms; robust | Alleviated anisotropy; high surface quality | FDM, WAAM, LDMD | Constraint optimization | Planner multi-axis; uniform | Volumes with non-shape edges | Anisotropy; easy to control toward 3+2-axis; not efficient | Alleviated anisotropy; weak stiffness | FDM | Curved layer decomposition | Nonplanar; nonuniform | Volumes with non-shape edges | Complex algorithms; not efficient | Isotropy; lower surfaces quality | FDM | Inner/outer volume decomposition | Planner multi-axis; uniform | Volumes with non-shape edges | Easy algorithms; efficient; easy to control | Isotropy; lower surfaces quality; few defects or voids in inner volume | WAAM, LDMD |
|
Table 4. Summary of process planning methods of multi-axis support-free 3D printing