• Chinese Journal of Lasers
  • Vol. 49, Issue 14, 1402302 (2022)
Jiangzhao Zhang, Huiliang Tang, Chu Wang, Xiaoxuan Wu, and Yu Long*
Author Affiliations
  • Institute of Laser Intelligent Manufacturing and Precision Processing, School of Mechanical Engineering, Guangxi University, Nanning 530004, Guangxi, China
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    DOI: 10.3788/CJL202249.1402302 Cite this Article Set citation alerts
    Jiangzhao Zhang, Huiliang Tang, Chu Wang, Xiaoxuan Wu, Yu Long. Latest Research Progress and Prospect of Process Planning Algorithms of Multiaxis Support-Free 3D Printing for Complex Structure[J]. Chinese Journal of Lasers, 2022, 49(14): 1402302 Copy Citation Text show less
    A general workflow of 3D printing preprocessing
    Fig. 1. A general workflow of 3D printing preprocessing
    Number of publications on multiaxis 3D printing[20]
    Fig. 2. Number of publications on multiaxis 3D printing[20]
    Non-uniform slicing method[30]
    Fig. 3. Non-uniform slicing method[30]
    Unit layer slicing method[31]. (a) Unit layer;(b) result of slicing; (c) unit layer after deposition
    Fig. 4. Unit layer slicing method[31]. (a) Unit layer;(b) result of slicing; (c) unit layer after deposition
    Offset slicing method[32]. (a) Base surface of contour; (b) offset slices obtained from base surface
    Fig. 5. Offset slicing method[32]. (a) Base surface of contour; (b) offset slices obtained from base surface
    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. 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
    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. 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
    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. 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
    Nonplanar slicing method proposed by Zhao et al[36]. (a) Decomposed volumes; (b) offset surfaces; (c) trimmed surfaces; (d) five-axis toolpaths
    Fig. 9. Nonplanar slicing method proposed by Zhao et al[36]. (a) Decomposed volumes; (b) offset surfaces; (c) trimmed surfaces; (d) five-axis toolpaths
    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. 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
    Illustration of method proposed by Wang et al[40]. (a) Input Y shape model; (b) three extracted skeletal polylines of S1γ, S2γ, and S3γ; (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 S4γ, as part of S3γ, is reserved B* after plane clipping, and a single skeleton S5γ is re-extracted from trunk model A*; (g) C, E, and G printed in fixed directions; (h) final decomposition result
    Fig. 11. Illustration of method proposed by Wang et al[40]. (a) Input Y shape model; (b) three extracted skeletal polylines of S1γ, S2γ, and S3γ; (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 S4γ, as part of S3γ, is reserved B* after plane clipping, and a single skeleton S5γ is re-extracted from trunk model A*; (g) C, E, and G printed in fixed directions; (h) final decomposition result
    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. 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)
    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. 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
    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. 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
    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. 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
    Illustrate of ellipsoid based curved slicing[57]. (a) A characteristic ellipsoid of a sub-entity; (b) intermediate ellipsoid generation
    Fig. 16. Illustrate of ellipsoid based curved slicing[57]. (a) A characteristic ellipsoid of a sub-entity; (b) intermediate ellipsoid generation
    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. 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
    Horizontal planes with equal distances h between each other generate different layer thicknesses in the welding direction[61]
    Fig. 18. Horizontal planes with equal distances h between each other generate different layer thicknesses in the welding direction[61]
    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. 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
    Illustrate of staircase effect under three conditions[23]. (a) P⊆Q; (b) Q⊆P; (c) P⊄Q
    Fig. 20. Illustrate of staircase effect under three conditions[23]. (a) PQ; (b) QP; (c) PQ
    Comparison of methods between planar slicing and slightly curved slicing[68]. (a) Planner slicing method; (b) slightly curved slicing method
    Fig. 21. Comparison of methods between planar slicing and slightly curved slicing[68]. (a) Planner slicing method; (b) slightly curved slicing method
    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. 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
    Slicing and path generation method and actual print results for RotBot[81]
    Fig. 23. Slicing and path generation method and actual print results for RotBot[81]
    Singularity aware motion planning[93]. (a) Singularity aware optimization is not used; (b) singularity aware optimization is used
    Fig. 24. Singularity aware motion planning[93]. (a) Singularity aware optimization is not used; (b) singularity aware optimization is used
    Original input modelDecomposed result by Wu et al[41]Decomposed result by Xu et al[45]Decomposed result by Xiao et al[46]
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    Table 1. Comparison of decomposition results based on constrained optimization methods[46]
    Ref.YearCategorySuitable type of modelsDecomposing with planes or surfacesLimitationPlatform typeDOF
    Dep.headBuild plate
    [41]2017Shape-analysis-based decomposition, constrained fine tuningMulti-branched structure; volumes with non-shape edgesPlanesRoot node of print sequence needs to be manually intervention6-DOF robotic arm03 trans., 3 orient.
    [42]2019Constrained optimization, heuristic search(ant colony algorithm)Volumes with non-shape edges; ring-like models(compared with results of Ref. [41])PlanesNumber of cutting planes need to be manually intervention; not efficient5-axis CNC machine3 trans.2 orient.
    [44]2019Constrained optimization, gravity-effect partitionOverhanging features with sharp concave edges or concave loopsPlanesSeveral type of workpieces like hollow cubic cannot be partitioned5-axis CNC machine3 trans.2 orient.
    [45]2019Constrained optimization, downward flooding searchTree structurePlanesSub-volumes which may interference with printing nozzle should be merged manually3 -axis(tested their method by assembly parts),--
    [43]2020Constrained optimization, beam-guided searchVolumes with non-shape edges (compared with results of Ref. [45])PlanesRotational axis should be chosen carefully6-DOF robotic arm03 trans., 3 orient.
    [46]2020Constrained optimizationOverhanging features with sharp concave edges or concave loops; ring-like models; volumes with non-shape edgesPlanes/surfacesRotational axis should be chosen carefully3 -axis (tested their method by assembly parts)--
    Table 2. Comparison of characteristics of constraint-based optimization methods
    Ref.YearCategorySuitable type of modelsLimitationPlatform typeDOF
    Generation method of initial curved layersGeneration method of curved toolpathClassification of curved toolpathOptimization method of orientation-smoothingDep. headBuild plate
    [47]2018Growing field generated by determining an order of voxel accumulationGenerated by FWP-MMP methodContinuous fermal spiral tool-pathLow pass filtering sampling; quaternion interpolationVolumes with non-shape edgesDiscretization error; Not efficient; Lower surfaces quality6-DOF robotic arm03 trans., 3 orient.
    [51]2019Scalar field computed based on MMP algorithmGeodesic distance field computed based on MMP methodContour-parallel path5-point sampling with Gaussian hemisphere interpolationVolumes with non-shape edgesPotential local interference; low productivity6-DOF robotic arm03 trans., 3 orient.
    [53]2020Geodesic distance field based on heat methodGeodesic distance field based on heat methodContour-parallel path-Multi-branched structureParts with complicated topologies may lead to collision5-axis printing system3 trans.3 trans., 3 orient.
    [55]2020Scalar-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 edgesSupports needed; low productivity5-axis CNC machine3 trans.2 orient.
    [56]2021Temperature field based on COMSOLBased on heat methodContour-parallel path-Overhanging features are sharp concave edges or concave loopsPotential local interference; not efficient5-axis printing system3 trans.2 orient.
    [57]2022Ellipsoidal slicingField based methodContour-parallel path(iso-cusp height printing path)-Volumes with non-shape edgesComplex algorithms; global interference is not considered5-axis printing system3 trans.3 trans., 3 orient.
    [58]2021----Thin-walled structureAffected by human experience6-DOF robotic arm03 trans., 3 orient.
    Table 3. Summary and comparison of methods based on curved layer decomposition
    MethodCategorySuitable type of modelsCharacteristicImpact of manufacturing processMain application
    Overhang structure decompositionPlanner multi-axisOverhanging features are sharp concave edges or concave loopsEasy to control; efficientAlleviated anisotropy; high surface qualityFDM, WAAM, LDMD
    SkeletonizationPlanner multi-axis; nonuniformMulti-branched or tree structureEasy algorithms; robustAlleviated anisotropy; high surface qualityFDM, WAAM, LDMD
    Constraint optimizationPlanner multi-axis; uniformVolumes with non-shape edgesAnisotropy; easy to control toward 3+2-axis; not efficientAlleviated anisotropy; weak stiffnessFDM
    Curved layer decompositionNonplanar; nonuniformVolumes with non-shape edgesComplex algorithms; not efficientIsotropy; lower surfaces qualityFDM
    Inner/outer volume decompositionPlanner multi-axis; uniformVolumes with non-shape edgesEasy algorithms; efficient; easy to controlIsotropy; lower surfaces quality; few defects or voids in inner volumeWAAM, LDMD
    Table 4. Summary of process planning methods of multi-axis support-free 3D printing
    Jiangzhao Zhang, Huiliang Tang, Chu Wang, Xiaoxuan Wu, Yu Long. Latest Research Progress and Prospect of Process Planning Algorithms of Multiaxis Support-Free 3D Printing for Complex Structure[J]. Chinese Journal of Lasers, 2022, 49(14): 1402302
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