RAG-Based Model Generation for 3D Printing Through Code Synthesis

Olupelumi Moses Kayode; Joseph Rafferty; José
and Fontecha Bravo

doi:10.1007/978-3-032-16995-2_19

RAG-Based Model Generation for 3D Printing Through Code Synthesis

Olupelumi Moses Kayode
, Joseph Rafferty
, José and Fontecha Bravo (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In recent years, Additive Manufacturing (AM;3D Printing), has experienced considerable growth as an alternative to traditional Subtractive Manufacturing (SM) methods, particularly for prototyping, but increasingly in largescale commercial applications. Advances in printing technology and reduction in material costs have driven this shift. Despite these advancements, challenges associated with generating printable three-dimensional models remain. This process can often be time-consuming and necessitates a high level of expertise. Consequently, there has been a marked interest in integrating generative artificial intelligence (AI) technologies to automate 3D model generation. This paper aims to develop a parameter-aware generative AI framework that synthesizes hollow 3D models of boxes, cylinders, cones, spheres and pyramids from textual descriptions while incorporating specifications for printability.

Original language	English
Title of host publication	Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2
Editors	José Bravo, Jesús Fontecha, Joaquín Ballesteros
Pages	203-215
Number of pages	13
Volume	2
ISBN (Electronic)	978-3-032-16995-2
DOIs	https://doi.org/10.1007/978-3-032-16995-2_19
Publication status	Published online - 1 Apr 2026
Event	The International Conference on Ubiquitous Computing and Ambient Intelligence - Fondazione PIN - Polo di Prato dell'Università di Firenze, Florence, Italy Duration: 26 Nov 2025 → 28 Nov 2025 Conference number: 17 https://www.ucami.org/

Publication series

Name	Lecture Notes in Networks and Systems
Publisher	Springer Nature
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	The International Conference on Ubiquitous Computing and Ambient Intelligence
Abbreviated title	UCAmI 2025
Country/Territory	Italy
City	Florence
Period	26/11/25 → 28/11/25
Internet address	https://www.ucami.org/

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 12 Responsible Consumption and Production

Keywords

3D Printing
Prompt Engineering
Generative AI
Additive Manufacturing
Computer-Aided Design
Fabrication Constraints
Retrieval-Augmented Generation
Large Language Models
Code Synthesis

Access to Document

10.1007/978-3-032-16995-2_19

https://link.springer.com/chapter/10.1007/978-3-032-16995-2_19

Cite this

Kayode, O. M., Rafferty, J., & Bravo, J. F. (Ed.) (2026). RAG-Based Model Generation for 3D Printing Through Code Synthesis. In J. Bravo, J. Fontecha, & J. Ballesteros (Eds.), Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2 (Vol. 2, pp. 203-215). (Lecture Notes in Networks and Systems). Advance online publication. https://doi.org/10.1007/978-3-032-16995-2_19

Kayode, Olupelumi Moses ; Rafferty, Joseph ; Bravo, José and Fontecha (Editor). / RAG-Based Model Generation for 3D Printing Through Code Synthesis. Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2. editor / José Bravo ; Jesús Fontecha ; Joaquín Ballesteros. Vol. 2 2026. pp. 203-215 (Lecture Notes in Networks and Systems).

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abstract = "In recent years, Additive Manufacturing (AM;3D Printing), has experienced considerable growth as an alternative to traditional Subtractive Manufacturing (SM) methods, particularly for prototyping, but increasingly in largescale commercial applications. Advances in printing technology and reduction in material costs have driven this shift. Despite these advancements, challenges associated with generating printable three-dimensional models remain. This process can often be time-consuming and necessitates a high level of expertise. Consequently, there has been a marked interest in integrating generative artificial intelligence (AI) technologies to automate 3D model generation. This paper aims to develop a parameter-aware generative AI framework that synthesizes hollow 3D models of boxes, cylinders, cones, spheres and pyramids from textual descriptions while incorporating specifications for printability.",

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Kayode, OM , Rafferty, J & Bravo, JF (ed.) 2026, RAG-Based Model Generation for 3D Printing Through Code Synthesis. in J Bravo, J Fontecha & J Ballesteros (eds), Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2. vol. 2, Lecture Notes in Networks and Systems, pp. 203-215, The International Conference on Ubiquitous Computing and Ambient Intelligence, Florence, Italy, 26/11/25. https://doi.org/10.1007/978-3-032-16995-2_19

RAG-Based Model Generation for 3D Printing Through Code Synthesis. / Kayode, Olupelumi Moses ; Rafferty, Joseph; Bravo, José and Fontecha (Editor).
Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2. ed. / José Bravo; Jesús Fontecha; Joaquín Ballesteros. Vol. 2 2026. p. 203-215 (Lecture Notes in Networks and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - RAG-Based Model Generation for 3D Printing Through Code Synthesis

AU - Kayode, Olupelumi Moses

AU - Rafferty, Joseph

A2 - Bravo, José and Fontecha

A2 - Bravo, José

A2 - Fontecha, Jesús

A2 - Ballesteros, Joaquín

N1 - Conference code: 17

PY - 2026/4/1

Y1 - 2026/4/1

N2 - In recent years, Additive Manufacturing (AM;3D Printing), has experienced considerable growth as an alternative to traditional Subtractive Manufacturing (SM) methods, particularly for prototyping, but increasingly in largescale commercial applications. Advances in printing technology and reduction in material costs have driven this shift. Despite these advancements, challenges associated with generating printable three-dimensional models remain. This process can often be time-consuming and necessitates a high level of expertise. Consequently, there has been a marked interest in integrating generative artificial intelligence (AI) technologies to automate 3D model generation. This paper aims to develop a parameter-aware generative AI framework that synthesizes hollow 3D models of boxes, cylinders, cones, spheres and pyramids from textual descriptions while incorporating specifications for printability.

AB - In recent years, Additive Manufacturing (AM;3D Printing), has experienced considerable growth as an alternative to traditional Subtractive Manufacturing (SM) methods, particularly for prototyping, but increasingly in largescale commercial applications. Advances in printing technology and reduction in material costs have driven this shift. Despite these advancements, challenges associated with generating printable three-dimensional models remain. This process can often be time-consuming and necessitates a high level of expertise. Consequently, there has been a marked interest in integrating generative artificial intelligence (AI) technologies to automate 3D model generation. This paper aims to develop a parameter-aware generative AI framework that synthesizes hollow 3D models of boxes, cylinders, cones, spheres and pyramids from textual descriptions while incorporating specifications for printability.

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KW - Prompt Engineering

KW - Generative AI

KW - Additive Manufacturing

KW - Computer-Aided Design

KW - Fabrication Constraints

KW - Retrieval-Augmented Generation

KW - Large Language Models

KW - Code Synthesis

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DO - 10.1007/978-3-032-16995-2_19

M3 - Conference contribution

SN - 9783032169945

VL - 2

T3 - Lecture Notes in Networks and Systems

SP - 203

EP - 215

BT - Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2

T2 - The International Conference on Ubiquitous Computing and Ambient Intelligence

Y2 - 26 November 2025 through 28 November 2025

ER -

Kayode OM , Rafferty J, Bravo JF, (ed.). RAG-Based Model Generation for 3D Printing Through Code Synthesis. In Bravo J, Fontecha J, Ballesteros J, editors, Proceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2025), Volume 2. Vol. 2. 2026. p. 203-215. (Lecture Notes in Networks and Systems). Epub 2026 Apr 1. doi: 10.1007/978-3-032-16995-2_19

RAG-Based Model Generation for 3D Printing Through Code Synthesis

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this