Advertisement

Impacts of the settings in a design for additive manufacturing process based on topological optimization

  • Elodie Morretton
  • Frédéric Vignat
  • Franck PourroyEmail author
  • Philippe Marin
Original Paper
  • 46 Downloads

Abstract

With the development of additive manufacturing technologies, designers are being offered new opportunities that are changing their usual design rules. The ability to create increasingly complex shapes constitutes the main opening. The complexity achieved makes it possible to obtain lightweight parts while maintaining high mechanical performance. As a result, design methods have to be adapted. Most of these methods include a design optimization phase to improve mechanical performance. Topological optimization tools are becoming essential to achieve this objective. They allow to achieve the best possible design as unnecessary material is stripped away leaving only that needed to meet the design requirements. Nevertheless, the designer continues to play a significant role in terms of the final design owing to the number of variables and settings involved in each stage of the design process. This paper uses a case study to assess the impacts on part geometry of the different design optimization settings used in the additive manufacturing process. It highlights how the settings adjustments made by the designer have a significant impact on the final design.

Keywords

Design process Topological optimization Additive manufacturing Settings 

Notes

References

  1. 1.
    Thompson, M.K., Moroni, G., Vaneker, T., Fadel, G., Campbell, R.I., Gibson, I., Bernard, A., Schulz, J., Graf, P., Ahuja, B., Martina, F.: Design for additive manufacturing: trends, opportunities, considerations, and constraints. CIRP Ann. Manuf. Technol. 65(2), 737–760 (2016)CrossRefGoogle Scholar
  2. 2.
    Conner, B.P., Manogharan, G.P., Martof, A.N., Rodomsky, L.M., Rodomsky, C.M., Jordan, D.C., Limperos, J.W.: Making sense of 3-D printing: creating a map of additive manufacturing products and services. Addit. Manuf. 1–4, 64–76 (2014)CrossRefGoogle Scholar
  3. 3.
    Laverne, F., Segonds, F., Anwer, N., Le Coq, M.: Assembly based methods to support product innovation in design for additive manufacturing: an exploratory case study. J. Mech. Des. 137(12), 121701–121709 (2015)CrossRefGoogle Scholar
  4. 4.
    Vayre, B.: Conception pour la fabrication additive, application à la technologie EBM, Université Grenoble Alpes (2014)Google Scholar
  5. 5.
    Seepersad, C.: Challenges and opportunities in design for additive manufacturing. 3D Print. Addit. Manuf. 1(1), 10–13 (2014)CrossRefGoogle Scholar
  6. 6.
    Emmelmann, C., Sander, P., Kranz, J., Wycisk, E.: Laser additive manufacturing and bionics: redefining lightweight design. Phys. Procedia 12, 364–368 (2011)CrossRefGoogle Scholar
  7. 7.
    Williams, C.B., Mistree, F., Rosen, D.W.: A functional classification framework for the conceptual design of additive manufacturing technologies. J. Mech. Des. 133(12), 121002 (2011)CrossRefGoogle Scholar
  8. 8.
    Gaynor, A.T., Guest, J.K.: Topology optimization considering overhang constraints: eliminating sacrificial support material in additive manufacturing through design. Struct. Multidiscip. Optim. 54(5), 1157–1172 (2016)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Ponche, R., Hascoet, J.-Y., Kerbrat, O., Mognol, P.: A new global approach to design for additive manufacturing. Virtual Phys. Prototyp. 7(2), 93–105 (2012)CrossRefGoogle Scholar
  10. 10.
    Galjaard, S., Hofman, S., Ren, S.: New opportunities to optimize structural designs in metal by using additive manufacturing. Adv. Archit. Geom. 2014, 79–93 (2014)Google Scholar
  11. 11.
    Leary, M., Merli, L., Torti, F., Mazur, M., Brandt, M.: Optimal topology for additive manufacture: a method for enabling additive manufacture of support-free optimal structures. Mater. Des. 63, 678–690 (2014)CrossRefGoogle Scholar
  12. 12.
    Dugré, A., Vadean, A., Chaussée, J.: Challenges of using topology optimization for the design of pressurized stiffened panels. Struct. Multidiscip. Optim. 53(2), 303–320 (2016)CrossRefGoogle Scholar
  13. 13.
    Nadeau, J.P., Fischer, X. (eds.): Research in interactive design (Vol. 3): virtual, interactive and integrated product design and manufacturing for industrial innovation. Springer, Berlin (2011)Google Scholar
  14. 14.
    Hsu, Y.-L., Hsu, M.-S., Chen, C.-T.: Interpreting results from topology optimization using density contours. Comput. Struct. 79(10), 1049–1058 (2001)CrossRefGoogle Scholar
  15. 15.
    Doutre, P., Morretton, E., Vo, T. H., Marin, P., Pourroy, F., Prudhomme, G., Vignat, F.: Comparison of some approaches to define a CAD model from topological optimization in design for additive manufacturing. In: Advances on Mechanics, Design Engineering and Manufacturing, pp. 233–240. (2016)Google Scholar
  16. 16.
    Rosen, D.W.: A review of synthesis methods for additive manufacturing. Virtual Phys. Prototyp. 11(4), 305–317 (2016)CrossRefGoogle Scholar
  17. 17.
    Rozvany, G.I.N.: A critical review of established methods of structural topology optimization. Struct. Multidiscip. Optim. 37(3), 217–237 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Wang, M.Y., Wang, X., Guo, D.: A level set method for structural topology optimization. Comput. Methods Appl. Mech. Eng. 192(1), 227–246 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Zhou, M., Shyy, Y.K., Thomas, H.L.: Checkerboard and minimum member size control in topology optimization. Struct. Multidiscip. Optim. 21(2), 152–158 (2001)CrossRefGoogle Scholar
  20. 20.
    Vayre, B., Vignat, F., Villeneuve, F.: Designing for additive manufacturing. Procedia CIRP 3(1), 632–637 (2012)CrossRefGoogle Scholar
  21. 21.
    Cuillière, J., Francois, V., Drouet, J.: Towards the integration of topology optimization into the CAD process. Comput. Aided Des. Appl. 11(2), 120–140 (2014)CrossRefGoogle Scholar
  22. 22.
    Sigmund, O., Petersson, J.: Numerical instabilities in topology optimization: a survey on procedures dealing with checkerboards, mesh-dependencies and local minima. Struct. Optim. 16(1), 68–75 (1998)CrossRefGoogle Scholar
  23. 23.
    Salonitis, K., Al Zarban, S.: Redesign optimization for manufacturing using additive layer techniques. Procedia CIRP 36, 193–198 (2015)CrossRefGoogle Scholar
  24. 24.
    Guest, J.K.: Imposing maximum length scale in topology optimization. Struct. Multidiscip. Optim. 37(5), 463–473 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Yang, S., Zhao, Y.F.: Additive manufacturing-enabled design theory and methodology: a critical review. Int. J. Adv. Manuf. Technol. 80(1–4), 327–342 (2015)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Larsen, S., Jensen, C.: Converting topology optimization results into parametric CAD models. Comput. Aided Des. Appl. 6(3), 407–418 (2009)CrossRefGoogle Scholar
  27. 27.
    Altair Engineering Inc. Optistruct 14.0 help files (2017)Google Scholar
  28. 28.
    Brown, K.S.: Euler characteristics of discrete groups and G-spaces. Inventiones Mathematicae 27(3), 229–264 (1974)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Univ. Grenoble Alpes, CNRS, Grenoble INP, G-SCOPGrenobleFrance
  2. 2.Zodiac Seats FranceIssoudunFrance

Personalised recommendations