| id |
caadria2018_270 |
| authors |
Houda, Maryam and Reinhardt, Dagmar |
| year |
2018 |
| title |
Structural Optimisation for 3D Printing Bespoke Geometries |
| source |
T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 235-244 |
| doi |
https://doi.org/10.52842/conf.caadria.2018.1.235
|
| summary |
Current advances in 3D printing technology enable novel design explorations with the potential to inform printing deposition through generative scripting and structural performance analysis. This paper presents ongoing research that involves three scales of operation; a global geometry for multi-skin cellular mesh densities; localised skin-porosity detailing, and material structural optimisation. Centering on a chair as a test case scenario, the research explores the affordances of a serialised, multi-material 3D printing process in the context of digital instruction, customisation, and material efficiency. The paper discusses two case studies with consecutive optimisation, and outlines the benefits and limitations of 3D printing for structural optimisation and multi-material grading in the additive process. |
| keywords |
3D Printing; Bespoke Complexity; Digital Instruction; Mass Customisation; Multi-Material Grading; Robotic Deposition; Structural Optimisation |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (10,731,818 bytes) |
| references |
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