Skip to main content

Path Optimization for Multi-material 3D Printing Using Self-organizing Maps

  • Conference paper
  • First Online:
Computer-Aided Architectural Design. Design Imperatives: The Future is Now (CAAD Futures 2021)

Abstract

Shape generation based on scalar fields opened up the space for new fabrication techniques bridging the digital and the physical through material computation. As an example, the development of voxelized methods for shape generation broadened the exploration of multi-material 3d printing and the use of Functionally Gradient Materials (FGM) through the creation of shapes based on their material properties known as Property representations (P-reps) as opposed to Boundary representations (B-reps) [1]. This paper proposes a novel approach for the fabrication of P-reps by generating optimized 3d printing paths by mapping shape internal stress into material distribution through a single optimized curve oriented to the fabrication of procedural shapes. By the use of a modified version of the traveling salesman problem (TSP), an optimized Spline is generated to map trajectories and material distribution into voxelized shape’s slices. As a result, we can obtain an optimized P-Rep G-code generation for multi-material 3d printing and explore the fabrication of P-Rep as FGMs based on material behavior.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Fusion deposition modeling.

  2. 2.

    https://github.com/tsamis/VSpace.

  3. 3.

    Michalatos, Panagiotis- Autodesk https://www.food4rhino.com/app/monolith.

  4. 4.

    In the experiments, we see that with the exception of the random distribution, the simple TSP performs poorly in length and self intersections number.

  5. 5.

    Through Radical component from Digital Space Exploration plugin for Grasshopper http://digitalstructures.mit.edu/page/tools#design-space-exploration-tool-suite-for-grasshopper.

  6. 6.

    Through Silvereye optimization plugin for Grasshopper. https://www.food4rhino.com/en/app/silvereye-pso-based-solver.

  7. 7.

    Through the use of Octopus for Grasshopper. https://www.food4rhino.com/en/app/octopus.

References

  1. Tsamis, A.: Software tectonics. Ph.D. thesis, MIT Department of Architecture, Cambridge, MA (2012)

    Google Scholar 

  2. By the use of software packages such as Vspace (Tsamis, Alexandros. https://github.com/tsamis/VSpace) or Monolith Michalatos, Panagiotis- Autodesk https://www.food4rhino.com/app/monolith

  3. Kaijima, Michalatos: Using millipede for topologycal optimization. http://www.sawapan.eu/

  4. Danhaive, R., Pinochet, D.: SKeXL, Sketch to Shape: A Generative design tool using three-dimensional generative adversarial networks by using user sketches to generate procedural shapes. https://diegopinochet.com/portfolio#42f7b021-2e36-42c0-9527-bf10495f2cd5

  5. Diego Pinochet (2019). https://diegopinochet.com/portfolio#2fa9c4d8-59d6-454c-b981-d84f2dba8cde

  6. Dreifus, G., et al.: 3D Print. Addit. Manuf. 98–104 (2017). https://doi.org/10.1089/3dp.2017.0007

  7. Castelino, K., D’Souza, R., Wright, P.K.: Toolpath optimization for minimizing airtime during machining. J. Manuf. Syst. 22(3), 173–180 (2003)

    Article  Google Scholar 

  8. Kohonen, T.: The self-organizing map. Neurocomputing 21(1), 1–6 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  9. Brocki, L.: Kohonen self-organizing map for the traveling salesperson. In: Traveling Salesperson Problem, Recent Advances in Mechatronics, pp. 116–119 (2010)

    Google Scholar 

  10. Michalatos and Payne. Working with Multi-scale Material Distributions. http://papers.cumincad.org/cgi-bin/works/Show?acadia13_043

  11. https://static1.squarespace.com/static/54450658e4b015161cd030cd/t/56ae214afd5d08a9013c99c0/1454252370968/Monolith_UserGuide.pdf

  12. ACADIA 14: Design Agency. In: Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA), Los Angeles, 23–25 October 2014, pp. 101–110 (2014). ISBN 9781926724478

    Google Scholar 

  13. Grigoriadis: Living systems and micro-utopias: towards continuous designing. In: Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016), Melbourne, 30 March–2 April 2016, pp. 589–598 (2016)

    Google Scholar 

  14. Oxman, N., Keating, S., Tsai, E.: Innovative Developments in Virtual and Physical Prototyping: In: Bártolo, P.J., et al. (eds.) Proceedings of VRAP: Advanced Research in Virtual and Rapid Prototyping. Taylor & Francis

    Google Scholar 

  15. Lechowicz, P., Koszalka, L., Pozniak-Koszalka, I., Kasprzak, A.: Path optimization in 3D printer: algorithms and experimentation system. In: 2016 4th International Symposium on Computational and Business Intelligence (ISCBI), Olten, pp. 137–142 (2016). https://doi.org/10.1109/ISCBI.2016.7743272

  16. Dreifus, G., et al.: Path optimization along lattices in additive manufacturing using the Chinese postman problem. 3D Print. Addit. Manuf. 4, 98–104 (2017). https://doi.org/10.1089/3dp.2017.0007

  17. Fok, K., Ganganath, N., Cheng, C., Tse, C.K.: A 3D printing path optimizer based on Christofides algorithm. In: 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), Nantou, pp. 1–2 (2016). https://doi.org/10.1109/ICCE-TW.2016.7520990

  18. Dreifus, G., et al.: 3D Print. Addit. Manuf. 98–104 (2017). https://doi.org/10.1089/3dp.2017.0007

  19. Kohonen: The self-organizing map. Neurocomputing 21(1), 1–6 (1998)

    Google Scholar 

  20. Brocki, Ł., Korzinek, D.: Kohonen Self-Organizing Map for the Traveling Salesperson Problem (2007). And Brocki, L. (2010).

    Google Scholar 

  21. Kohonen: Self-organizing map for the traveling salesperson. In: Traveling Salesperson Problem, Recent Advances in Mechatronics, pp. 116–119

    Google Scholar 

  22. Kaijima, S., Michalatos, P.: Intuitive material distributions, Architectural Design (2011). Millipede. An analysis and optimization tool. http://www.sawapan.eu/ based on the work shown in

  23. Chaikin, G.M.: An algorithm for high-speed curve generation. Comput. Graph. Image Process. 3(4), 346–349 (1974)

    Article  Google Scholar 

  24. Implemented using RADICAL, a component part of the DSE toolkit. http://digitalstructures.mit.edu/page/tools#design-space-exploration-tool-suite-for-grasshopper

  25. https://en.wikipedia.org/wiki/Christofides_algorithm

  26. https://towardsdatascience.com/how-to-solve-the-traveling-salesman-problem-a-comparative-analysis-39056a916c9f

Download references

Acknowledgements

I would like to thank Dr. Caitlin Mueller and Yijiang Huang for all the support and great lectures at 4.450 Computational Structural design and Optimization at MIT. Their knowledge and dedication motivated me to propose and develop an atypical project that helped me move forward with important areas of my Ph.D. research. Also, I would like to thank the Design and Computation group at MIT and the school of design of Adolfo Ibañez University for their valuable support.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Diego Pinochet or Alexandros Tsamis .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pinochet, D., Tsamis, A. (2022). Path Optimization for Multi-material 3D Printing Using Self-organizing Maps. In: Gerber, D., Pantazis, E., Bogosian, B., Nahmad, A., Miltiadis, C. (eds) Computer-Aided Architectural Design. Design Imperatives: The Future is Now. CAAD Futures 2021. Communications in Computer and Information Science, vol 1465. Springer, Singapore. https://doi.org/10.1007/978-981-19-1280-1_21

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1280-1_21

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1279-5

  • Online ISBN: 978-981-19-1280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics