Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms

Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms

Abstract The choice of the optimal printing setup for Fused Deposition Modeling (FDM) 3D-printing technology is challenging due to complex interactions between process parameters and mechanical properties. This especially affects engineering applications where the maximum performance is required. To...

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Bibliographic Details
Main Authors: Antonio Panico, Alberto Corvi, Luca Collini, Corrado Sciancalepore
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Additive Manufacturing
Design-of-Experiments (DoE)
Random Forest
NSGA-II
Online Access:https://doi.org/10.1038/s41598-025-01016-z
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https://doi.org/10.1038/s41598-025-01016-z

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