Abstract
The transformation in manufacturing capability being driven by new processes, such as additive manufacturing, offers huge potential for product innovation and opportunity to create bespoke designs tailored to individual specifications or needs. However, current design systems and tools are not yet capable of fully capitalising on these new technologies and new approaches are needed. Many current methodologies are top-down and sequential, offering limited flexibility and an overly constrained design space. Post processing is needed ensure a design can be manufactured. This work presents a novel bottom-up methodology to generate designs that can be tightly integrated with the additive manufacturing environment and that can respond flexibly to changes in that environment. Focusing on overhang as an exemplar manufacturing constraint, the method engenders changes in the design either by locally adjusting the geometry to stay within limits or by adding an appropriate support structure. The method is bio-inspired, based on strategies observed in natural systems, particularly in biological growth and development. The design geometry is grown in a CAD based, bio-inspired generative design system called “Biohaviour”. This process is similar to plant growth, and the design’s final configuration, shape and size are informed by both the manufacturing capability and internal design stresses. The approach is demonstrated for overhang limit and build orientation and is extensible to any general situation.
Original language | English |
---|---|
Pages (from-to) | 463–479 |
Journal | Journal of Computational Design and Engineering |
Volume | 9 |
Issue number | 2 |
Early online date | 12 Mar 2022 |
DOIs | |
Publication status | Published - 01 Apr 2022 |
Keywords
- Engineering Design
- Design
- CAD
- Simulation
- Analysis
- Bioinspired
- Aerospace
Fingerprint
Dive into the research topics of 'Generative design for additive manufacturing using a biological development analogy'. Together they form a unique fingerprint.Student theses
-
Goal-driven design in a bio-inspired system
Kyle, S. R. (Author), Nolan, D. (Supervisor), Price, M. (Supervisor) & Zhang, W. (Supervisor), Jul 2023Student thesis: Doctoral Thesis › Doctor of Philosophy
File