Advancing Metal Additive Manufacturing: A Review of Numerical Methods in DED, WAAM, and PBF

Advancing Metal Additive Manufacturing: A Review of Numerical Methods in DED, WAAM, and PBF

Metal additive manufacturing (AM) techniques such Direct Energy Deposition (DED), Powder Bed Fusion (PBF), and Wire Arc Additive Manufacturing (WAAM) enable the production of complex metal components built at rapid rates. Because of the complexity of the process, including high thermal gradients, re...

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Bibliographic Details
Main Authors: Allen Love, Omar Alejandro Valdez Pastrana, Saeed Behseresht, Young Ho Park
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Metrology
Subjects:
additive manufacturing
direct energy deposition
powder bed fusion
wire arc additive manufacturing
numerical modeling
finite element analysis
Online Access:https://www.mdpi.com/2673-8244/5/2/30
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Summary:Metal additive manufacturing (AM) techniques such Direct Energy Deposition (DED), Powder Bed Fusion (PBF), and Wire Arc Additive Manufacturing (WAAM) enable the production of complex metal components built at rapid rates. Because of the complexity of the process, including high thermal gradients, residual stress, and parameter optimization, these techniques pose significant challenges necessitating the need for advanced computational modeling. A powerful technique to reduce or, in some cases, eliminate these challenges at a much lower cost compared to trial-and-error experiments, is Finite Element Analysis (FEA). This study provides a comprehensive review of the FEA techniques being used and developed to model metal AM processes focusing on the thermal, mechanical, and coupled thermo-mechanical models in DED, PBF, and WAAM. Key topics include heat transfer, residual stress and distortion prediction, microstructure evolution and parameter optimization. Recent advancements in FEA have improved the accuracy of AM process simulations, reducing the need for costly experimental testing, though there is still room for improvement and further development of FEA in metal AM. This review serves as a foundation for future work in the metal AM modeling field, enabling the development of optimized process parameters, defect reduction strategies and improved computational methodologies for high-fidelity simulations.
ISSN:2673-8244

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