Skip to main content
SpringerLink
Log in

Cross section-based hollowing and structural enhancement

  • Original Article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Recently, 3D printing has become a powerful tool for personal fabrication. However, the price of some materials is still high which limits its applications in home users. To optimize the volume of the model, while not largely affecting the strength of the objects, researchers propose algorithms to divide the model with different kinds of lightweight structures, such as frame structure, honeycomb cell structure, truss structure, medial axis tree. However, these algorithms are not suitable for the model whose internal space needs to be reused. In addition, the structural strength and static stability of the models, obtained with modern 3D model acquirement methods, are not guaranteed. In consequence, some models are too fragile to print and cannot be survived in daily usage, handling, and transportation or cannot stand in a stable. To handle the mentioned problems, an algorithm system is proposed based on cross sections in this work. The structural weak cross sections are enhanced, and structural strong cross sections are adaptively hollowed to meet a given structural strength, static stability, printability, etc., while the material usage is minimized. The proposed algorithm system has been tested on several typical 3D models. The experimental results demonstrate the effectiveness and practicability of our system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Bächer, M., Bickel, B., James, D.L., Pfister, H.: Fabricating articulated characters from skinned meshes. ACM Trans. Graph. (TOG) 31(4), 47 (2012)

    Article  Google Scholar 

  2. Bächer, M., Whiting, E., Bickel, B., Sorkine-Hornung, O.: Spin-it: optimizing moment of inertia for spinnable objects. ACM Trans. Graph. (TOG) 33(4), 96 (2014)

    Article  Google Scholar 

  3. Cacciola, F.: 2D straight skeleton and polygon offsetting. In: CGAL User and Reference Manual, 4.2 edn. CGAL Editorial Board (2013)

  4. Ceylan, D., Li, W., Mitra, N.J., Agrawala, M., Pauly, M.: Designing and fabricating mechanical automata from mocap sequences. ACM Trans. Graph. (TOG) 32(6), 186 (2013)

    Article  Google Scholar 

  5. Chen, Y., Wang, C.C.: Uniform offsetting of polygonal model based on layered depth-normal images. Comput.-Aided Des. 43(1), 31–46 (2011)

    Article  Google Scholar 

  6. Cura: 3d printing software—cura. https://ultimaker.com/en/products/cura-software, year = 2016

  7. Dumas, J., Hergel, J., Lefebvre, S.: Bridging the gap: automated steady scaffoldings for 3d printing. ACM Trans. Graph. (TOG) 33(4), 98 (2014)

    Article  Google Scholar 

  8. Fu, H., Cohen-Or, D., Dror, G., Sheffer, A.: Upright orientation of man-made objects. In: ACM Transactions on Graphics (TOG), vol. 27, p. 42. ACM (2008)

  9. Gottschalk, S., Lin, M.C., Manocha, D.: Obbtree: a hierarchical structure for rapid interference detection. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 171–180. ACM (1996)

  10. Hildebrand, K., Bickel, B., Alexa, M.: Orthogonal slicing for additive manufacturing. Comput. Graph. 37(6), 669–675 (2013)

    Article  Google Scholar 

  11. Hoffmann, C.M.: Geometric and Solid Modeling (1989)

  12. Kim, S.J., Lee, D.Y., Yang, M.Y.: Offset triangular mesh using the multiple normal vectors of a vertex. Comput.-Aided Des. Appl. 1(1–4), 285–291 (2004)

    Article  Google Scholar 

  13. Liu, S., Wang, C.C.: Fast intersection-free offset surface generation from freeform models with triangular meshes. IEEE Trans. Autom. Sci. Eng. 8(2), 347–360 (2011)

    Article  MathSciNet  Google Scholar 

  14. Lu, L., Sharf, A., Zhao, H., Wei, Y., Fan, Q., Chen, X., Savoye, Y., Tu, C., Cohen-Or, D., Chen, B.: Build-to-last: strength to weight 3d printed objects. ACM Trans. Graph. (TOG) 33(4), 97 (2014)

    Google Scholar 

  15. Makerbot: Rapid prototyping and 3D printing. http://www.makerbot.com/ (2012)

  16. Makerware: 3d printing software—makerware. http://www.makerbot.com/blog/2013/12/09/makerbot-makerware-2-4-1-release, year = 2016

  17. Meyers, D., Skinner, S., Sloan, K.: Surfaces from contours. ACM Trans. Graph. (TOG) 11(3), 228–258 (1992)

    Article  MATH  Google Scholar 

  18. Musialski, P., Auzinger, T., Birsak, M., Wimmer, M., Kobbelt, L.: Reduced-order shape optimization using offset surfaces. ACM Trans. Graph. 34(4), 102 (2015)

    Article  MATH  Google Scholar 

  19. Musialski, P., Hafner, C., Rist, F., Birsak, M., Wimmer, M., Kobbelt, L.: Non-linear shape optimization using local subspace projections. ACM Trans. Graph. 35(4) (2016)

  20. Nocedal, J., Wright, S.: Numerical optimization. Springer, New York (2006)

    MATH  Google Scholar 

  21. Pintus, R., Gobbetti, E., Cignoni, P., Scopigno, R.: Shape enhancement for rapid prototyping. Vis. Comput. 26(6–8), 831–840 (2010)

    Article  Google Scholar 

  22. Porumbescu, S.D., Budge, B., Feng, L., Joy, K.I.: Shell maps. ACM Trans. Graph. 24(3), 626–633 (2005). doi:10.1145/1073204.1073239

    Article  Google Scholar 

  23. Prévost, R., Whiting, E., Lefebvre, S., Sorkine-Hornung, O.: Make it stand: balancing shapes for 3d fabrication. ACM Trans. Graph. (TOG) 32(4), 81 (2013)

    Article  MATH  Google Scholar 

  24. e Sá, A.M., Mello, V.M., Echavarria, K.R., Covill, D.: Adaptive voids. Vis. Comput. 31(6–8), 799–808 (2015)

    Google Scholar 

  25. Schmidt, R., Umetani, N.: Branching support structures for 3d printing. In: ACM SIGGRAPH 2014 Studio, p. 9. ACM (2014)

  26. Sorkine, O., Alexa, M.: As-rigid-as-possible surface modeling. In: Proceedings of EUROGRAPHICS/ACM SIGGRAPH Symposium on Geometry Processing, pp. 109–116 (2007)

  27. Stava, O., Vanek, J., Benes, B., Carr, N., Měch, R.: Stress relief: improving structural strength of 3D printable objects. ACM Transactions on Graphics (Proc. SIGGRAPH) 31(4), 48:1–11 (2012)

  28. Sun, T., Zheng, C., Zhang, Y., Yin, C., Zheng, C., Zhou, K., Yue, Y., Smith, B., Batty, C., Xu, Z., et al.: Computational design of twisty joints and puzzles. ACM Trans. Graph. (TOG) 34(4), 101 (2015)

    Article  Google Scholar 

  29. Umetani, N., Schmidt, R.: Cross-sectional structural analysis for 3d printing optimization. SIGGRAPH Asia 5, 1–4 (2013)

    Google Scholar 

  30. Vanek, J., Galicia, J., Benes, B.: Clever support: efficient support structure generation for digital fabrication. In: Computer Graphics Forum, vol. 33, pp. 117–125. Wiley Online Library (2014)

  31. Vanek, J., Galicia, J., Benes, B., Měch, R., Carr, N., Stava, O., Miller, G.: Packmerger: a 3d print volume optimizer. Comput. Graph. Forum 33(6), 322–332 (2014)

    Article  Google Scholar 

  32. Wang, C.C., Manocha, D.: Gpu-based offset surface computation using point samples. Comput.-Aided Des. 45(2), 321–330 (2013)

    Article  MathSciNet  Google Scholar 

  33. Wang, L., Whiting, E.: Buoyancy optimization for computational fabrication. In: Computer Graphics Forum, vol. 35, pp. 49–58. Wiley Online Library (2016)

  34. Wang, W., Chao, H., Tong, J., Yang, Z., Tong, X., Li, H., Liu, X., Liu, L.: Saliency-preserving slicing optimization for effective 3d printing. In: Computer Graphics Forum, vol. 34, pp. 148–160. Wiley Online Library (2015)

  35. Wang, W., Liu, X., Liu, L.: Upright orientation of 3d shapes via tensor rank minimization. J. Mech. Sci. Technol. 28(7), 2469–2477 (2014)

    Article  Google Scholar 

  36. Wang, W., Wang, T.Y., Yang, Z., Liu, L., Tong, X., Tong, W., Deng, J., Chen, F., Liu, X.: Cost-effective printing of 3d objects with skin-frame structures. ACM Trans. Graph. (TOG) 32(6), 177 (2013)

    Google Scholar 

  37. Wang, W.M., Zanni, C., Kobbelt, L.: Improved surface quality in 3d printing by optimizing the printing direction. In: Computer Graphics Forum, vol. 35, pp. 59–70. Wiley Online Library (2016)

  38. Xie, Y., Xu, W., Yang, Y., Guo, X., Zhou, K.: Agile structural analysis for fabrication-aware shape editing. Comput. Aided Geom. Des. 35, 163–179 (2015)

    Article  MathSciNet  Google Scholar 

  39. Xu, W., Li, W., Liu, L.: Skeleton-sectional structural analysis for 3d printing. J. Comput. Sci. Technol. (In press) 31(3) (2016)

  40. Yamanaka, D., Suzuki, H., Ohtake, Y.: Density aware shape modeling to control mass properties of 3d printed objects. In: SIGGRAPH Asia 2014 Technical Briefs, p. 7. ACM (2014)

  41. Zhang, X., Le, X., Wu, Z., Whiting, E., Wang, C.C.L.: Data-driven bending elasticity design by shell thickness. Comput. Graph. Forum 35(5), 157–166 (2016)

    Article  Google Scholar 

  42. Zhang, X., Xia, Y., Wang, J., Yang, Z., Tu, C., Wang, W.: Medial axis treełan internal supporting structure for 3d printing. Comput. Aided Geom. Des. 35, 149–162 (2015)

  43. Zhao, H., Xu, W., Zhou, K., Yang, Y., Jin, X., Wu, H.: Stress-constrained thickness optimization for shell object fabrication. In: Computer Graphics Forum. Wiley Online Library (2016)

  44. Zhou, Q., Panetta, J., Zorin, D.: Worst-case structural analysis. ACM Trans. Graph. (TOG) 32(4), 137 (2013)

    MATH  Google Scholar 

  45. Zhu, L., Xu, W., Snyder, J., Liu, Y., Wang, G., Guo, B.: Motion-guided mechanical toy modeling. ACM Trans. Graph. 31(6), 127 (2012)

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank the reviewers for their detailed comments and suggestions which greatly improved the manuscript. The research leading to these results has received funding from China Postdoctoral Science Foundation (2016M601308), the One Hundred Talent Project of the Chinese Academy of Sciences, Fundamental Research Fund (DUT16RC(3)061), National Natural Science Foundation of China (61370143, 61432003, 61661130156, 61672482, 11626253, 11472073 ), Hong Kong RGC GRF (14207414), and Royal Society-Newton Advanced Fellowship (NA150431).

Author information

Authors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Weiming Wang, Baojun Li, Sicheng Qian, Baocai Yin & Xiuping Liu

  2. Tsinghua University, Beijing, China

    Yong-Jin Liu

  3. Delft University of Technology, Delft, Netherlands

    Charlie C. L. Wang

  4. University of Science and Technology of China, Hefei, China

    Ligang Liu

Authors
  1. Weiming Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Baojun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sicheng Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yong-Jin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Charlie C. L. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ligang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Baocai Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xiuping Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiuping Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, W., Li, B., Qian, S. et al. Cross section-based hollowing and structural enhancement. Vis Comput 33, 949–960 (2017). https://doi.org/10.1007/s00371-017-1386-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-017-1386-5

Keywords

Search

Navigation