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GrowCAD: bioinspired mathematical design for additive manufacturing.

Nasim Mahmoodi¹, Galane Jingxi Luo², Rosemary Julia Dyson²

¹School of Engineering, University of Birmingham, Birmingham, UK.

Royal Society Open Science

|September 26, 2025

Summary

This study introduces GrowCAD™, a novel design framework inspired by plant growth for additive manufacturing (AM). It enhances engineer creativity and simplifies the design process for complex AM geometries.

Keywords:

3D printing additive manufacturing bioinspired engineering design mathematical biology

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Area of Science:

Engineering
Computer Science
Biomimetics

Background:

Additive Manufacturing (AM) offers significant benefits but faces challenges in design implementation.
Current AM design processes are complex, involving geometry representation, software, and human problem-solving.
Enhancing engineer knowledge and creativity is crucial for overcoming design limitations.

Purpose of the Study:

To develop a novel design framework for Additive Manufacturing.
To enhance human knowledge and creativity in AM design.
To address the challenges of geometry representation and manufacturability in AM.

Main Methods:

A bioinspired methodology is introduced, using plant growth as an analogy for the layer-by-layer AM process.
Development of a novel length-polar-projection coordinate system and algebraic definitions for geometric features.
Creation of the GrowCAD™ design framework based on this mathematical representation.

Main Results:

The GrowCAD™ framework enables manufacturability analysis, parametric editability, and CAD compatibility.
Qualitative analysis validated shape fidelity, efficiency, detection of non-manufacturable geometry, and printability.
The developed system successfully generated and printed complex geometries.

Conclusions:

GrowCAD™ provides a simplified and intuitive method to enhance engineer knowledge and creativity in AM design.
The algebraic geometry representation facilitates manufacturability analysis and design iterations.
This bioinspired approach offers a promising solution for wider AM implementation.