Emerging Applications of Machine Learning in 3D Printing

Three-dimensional (3D) printing techniques already enable the precise deposition of many materials, becoming a promising approach for materials engineering, mechanical engineering, or biomedical engineering. Recent advances in 3D printing enable scientists and engineers to create models with precisely controlled and complex microarchitecture, shapes, and surface finishes, including multi-material printing. The incorporation of artificial intelligence (AI) at various stages of 3D printing has made it possible to reconstruct objects from images (including, for example, medical images), select and optimize materials and the printing process, and monitor the lifecycle of products. New emerging opportunities are provided by the ability of machine learning (ML) to analyze complex data sets and learn from previous (historical) experience and predictions to dynamically optimize and individuate products and processes. This includes the synergistic capabilities of 3D printing and ML for the development of personalized products.

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Publication Details

Journal
Applied Sciences
Published
2025-02-10
DOI
https://doi.org/10.3390/app15041781
Citations
22
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
15.02

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article

Emerging Applications of Machine Learning in 3D Printing

Marcin Kempiński, Izabela Rojek, Dariusz Mikołajewski, Adrianna Piszcz et al.
22 citations
Applied Sciences
Additive Manufacturing and 3D Printing Technologies
15.02
article

Emerging Applications of Machine Learning in 3D Printing

Marcin Kempiński, Izabela Rojek, Dariusz Mikołajewski, Adrianna Piszcz, Krzysztof Galas
article en
22 citations

Abstract

Three-dimensional (3D) printing techniques already enable the precise deposition of many materials, becoming a promising approach for materials engineering, mechanical engineering, or biomedical engineering. Recent advances in 3D printing enable scientists and engineers to create models with precisely controlled and complex microarchitecture, shapes, and surface finishes, including multi-material printing. The incorporation of artificial intelligence (AI) at various stages of 3D printing has made it possible to reconstruct objects from images (including, for example, medical images), select and optimize materials and the printing process, and monitor the lifecycle of products. New emerging opportunities are provided by the ability of machine learning (ML) to analyze complex data sets and learn from previous (historical) experience and predictions to dynamically optimize and individuate products and processes. This includes the synergistic capabilities of 3D printing and ML for the development of personalized products.

Applied SciencesVol. 15(4)
Kazimierz Wielki University in Bydgoszcz (PL)
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Openalex Percentile: Top 1%
Additive Manufacturing and 3D Printing Technologies
15.02
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Emerging Applications of Machine Learning in 3D Printing — Marcin Kempiński, Izabela Rojek, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS