Page 36 - ESAM-1-1

Engineering Science in

Additive Manufacturing

REVIEW ARTICLE
Generative artificial intelligence in lattice

structure design for additive manufacturing: A
critical review

Jinlong Su* , Yang Mo, and Swee Leong Sing*

Department of Mechanical Engineering, College of Design and Engineering, National University of
Singapore, Singapore

Abstract

Lattice structures, characterized by their lightweight yet high-strength properties,
energy absorption capabilities, and superior thermal management, have become
integral in advanced additive manufacturing (AM) applications. However, designing
optimized lattice structures that balance mechanical performance, manufacturability,
and functional requirements remains a complex and computationally intensive
challenge. Recently, generative artificial intelligence (Gen-AI) has emerged as a
transformative approach, offering automated and efficient solutions for lattice
structure design. This review explores the application of Gen-AI in lattice structure
*Corresponding authors: design and optimization for AM. Gen-AI enables automated inverse design,
Jinlong Su generating lattice structures that meet predefined functional and mechanical
(jinlongsu96@foxmail.com) targets, reducing trial-and-error efforts. It supports performance optimization by
Swee Leong Sing
(sweeleong.sing@nus.edu.sg) enhancing mechanical strength, energy absorption, and thermal efficiency when
minimizing material usage and weight. Besides, Gen-AI also facilitates process-aware
Citation: Su J, Mo Y, Sing SL. design by integrating AM-oriented constraints, such as build orientation, support
Generative artificial intelligence
in lattice structure design for strategies, and residual stress, to improve manufacturability and reduce post-
additive manufacturing: A critical processing. In addition, it accelerates simulations by expediting performance
review. Eng Sci Add Manuf. prediction and reducing computational costs. Despite the growing importance of
2025;1(1):025110006.
doi: 10.36922/ESAM025110006 Gen-AI in AM lattice structure, comprehensive reviews on this topic remain limited.
This work addresses this gap, providing critical insights into current advancements,
Received: February 8, 2025
key challenges, and future perspectives, aiming to guide the integration of Gen-AI
1st revised: March 3, 2025 into advanced lattice structure design for AM and support the development of
2nd revised: March 17, 2025 next-generation high-performance structures.
Accepted: March 18, 2025
Published online: March 21, 2025 Keywords: Generative artificial intelligence; Lattice structure; Additive manufacturing;
Deep learning; Design and optimization
Copyright: © 2025 Author(s).
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution
License, permitting distribution, 1. Introduction
and reproduction in any medium,
provided the original work is Lattice structures are periodic cellular networks (often crisscross patterns of struts
properly cited. or walls) that offer exceptional properties: they are lightweight yet strong, can absorb
Publisher’s Note: AccScience energy, reduce vibration, and dissipate heat more effectively than solid forms.
1,2
Publishing remains neutral with Additive manufacturing (AM) enables the fabrication of complex geometries layer by
regard to jurisdictional claims in
published maps and institutional layer, including intricate lattice structures that were once impossible to produce with
affiliations. traditional manufacturing. These advantages have led to widespread use of lattices in
3-7
Volume 1 Issue 1 (2025) 1 doi: 10.36922/ESAM025110006