An automatic optimization method for minimizing supporting structures in additive manufacturing

  • Xiao-Jun ChenEmail author
  • Jun-Lei Hu
  • Qing-Long Zhou
  • Constantinus Politis
  • Yi Sun


The amount of supporting structure usage has been a major research topic in layer-based additive manufacturing (AM) over the past years as it leads to increased fabrication time and decreased surface quality. Previous studies focused on deformation and topology optimization to eliminate the number of support structures. However, during the actual fabrication process, the properties of shape and topology are essential. Therefore, they should not be modified casually. In this study, we present an optimizer that reduces the number of supporting structures by identifying the prime printing direction. Without rotation, models are projected in each direction in space, and the basis units involved in the generation of support structures are separated. Furthermore, the area of the supporting structures is calculated. Eventually, the prime printing direction with minimal supporting area is obtained through pattern-searching method. The results of the experiment demonstrated that the printing area was reduced by up to 60% for some cases, and the surface quality was also improved correspondingly. Furthermore, both the material consumption and fabrication time were decreased in most cases. In future work, additional factors will be considered, such as the height of the supporting structures and the adhesion locations to improve the efficiency of this optimizer.


Printing direction Optimization Supporting structures 



This work was supported from the National Key R&D Program of China (Grant No. 2017YFB1104100), the National Natural Science Foundation of China (Grant Nos. 81971709, 81828003), the Foundation of Ministry of Education of China Science and Technology Development Center (Grant No. 2018C01038), the Foundation of Science and Technology Commission of Shanghai Municipality (Grant Nos. 19510712200, 16441908400), and Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research (Grant Nos. YG2016ZD01, ZH2018ZDA15).


  1. 1.
    Cunico MWM (2011) Development of new rapid prototyping process. Rapid Prototyp J 17:138–147CrossRefGoogle Scholar
  2. 2.
    Jin Y, He Y (2014) Optimization of tool-path generation for material extrusion-based additive manufacturing technology. Addit Manuf 1/4:32–47CrossRefGoogle Scholar
  3. 3.
    Pereira S, Vaz AIF, Vicente LN (2018) On the optimal object orientation in additive manufacturing. Int J Adv Manuf Technol 98:1685–1694CrossRefGoogle Scholar
  4. 4.
    Cheng W, Fuh JYH, Nee AYC et al (1995) Multi-objective optimization of part building orientation in stereolithography. Rapid Prototyp J 1(4):12–23CrossRefGoogle Scholar
  5. 5.
    Hu K, Jin S, Wang CCL (2015) Supporting slimming for single material based additive manufacturing. Comput Aided Des 65:1–10CrossRefGoogle Scholar
  6. 6.
    Jiang J, Xu X, Stringer J (2018) Support structures for additive manufacturing: a review. J Manuf Mater Process 2(4):64Google Scholar
  7. 7.
    Tay YWD, Li MY, Tan MJ (2019) Effect of printing parameters in 3D concrete printing: printing region and support structures. J Mater Process Technol 271:261–270CrossRefGoogle Scholar
  8. 8.
    Gao W (2015) The status, challenges, and future of additive manufacturing in engineering. Comput Aided Des 69:65–89CrossRefGoogle Scholar
  9. 9.
    Stava O, Vanek J, Benes B (2012) Stress relief: improving structural strength of 3D printable objects. ACM Trans Graph 31(4):1–11CrossRefGoogle Scholar
  10. 10.
    Luo L, Baran I, Rusinkiewicz S et al (2012) Chopper: partitioning models into 3D-printable parts. ACM Trans Graph 31(6):1–9Google Scholar
  11. 11.
    Chen D, Levin D, Didyk P et al (2013) Spec2Fab: a reducer-tuner model for translating specifi cations to 3D prints. ACM Trans Graph 32(4):1–9Google Scholar
  12. 12.
    Paul R, Anand S (2015) Optimization of layered manufacturing process for reducing form errors with minimal support structures. J Manuf Syst 35:231–243CrossRefGoogle Scholar
  13. 13.
    Leary M, Merli L, Torti F et al (2014) Optimal topology for additive manufacture: a method for enabling additive manufacture of support-free optimal structures. Mater Des 63:678–690CrossRefGoogle Scholar
  14. 14.
    Prévost R, Whiting E, Lefebvre S et al (2013) Make it stand: balancing shapes for 3D fabrication. ACM Trans Graph 32(4):1–10zbMATHCrossRefGoogle Scholar
  15. 15.
    Wang W, Wang TY, Yang Z et al (2013) Cost-effective printing of 3D objects with skin-frame structures. ACM Trans Graph 32(6):1–10Google Scholar
  16. 16.
    Chen Y (1997) Determining parting direction based on minimum bounding box and fuzzy logics. Int J Mach Tools Manuf 37(9):1189–1199CrossRefGoogle Scholar
  17. 17.
    Priyadarshi AK, Gupta SK (2006) Finding mold-piece regions using computer graphics hardware. Lect Notes Comput Sci 4077:655–662zbMATHCrossRefGoogle Scholar
  18. 18.
    Khardekar R, Burton G, McMains S (2006) Finding feasible mold parting directions using graphics hardware. Comput Aided Des 38(4):327–341CrossRefGoogle Scholar
  19. 19.
    Li W, Martin R, Langbein FC (2009) Molds for meshes: computing smooth parting lines and undercut removal. IEEE Trans Autom Sci Eng 6(3):423–432CrossRefGoogle Scholar
  20. 20.
    Cheng B, Chou K (2015) Geometric consideration of support structures in part overhang fabrications by electron beam additive manufacturing. Comput Aided Des 69:102–111CrossRefGoogle Scholar
  21. 21.
    Giannitelli SM, Mozetic P, Trombetta M et al (2015) Combined additive manufacturing approaches in tissue engineering. Acta Biomater 24:1–11CrossRefGoogle Scholar
  22. 22.
    Tyberg J, Bohn JH (1999) FDM systems and local adaptive slicing. Mater Des 20(2/3):77–82CrossRefGoogle Scholar
  23. 23.
    Huang P, Wang CCL, Chen Y (2014) Algorithms for layered manufacturing in image space. Adv Comput Inf Eng Res 1:377–410Google Scholar
  24. 24.
    Chen Y, Li K, Qian X (2013) Direct geometry processing for tele-fabrication. J Comput Inf Sci Eng 13(4):1–18Google Scholar

Copyright information

© Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiao-Jun Chen
    • 1
    Email author
  • Jun-Lei Hu
    • 1
  • Qing-Long Zhou
    • 1
  • Constantinus Politis
    • 2
    • 3
  • Yi Sun
    • 2
    • 3
  1. 1.Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghaiP.R. China
  2. 2.OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of MedicineKatholieke Universiteit LeuvenLeuvenBelgium
  3. 3.Department of Oral and Maxillofacial SurgeryUniversity Hospitals LeuvenLeuvenBelgium

Personalised recommendations