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Transforming Additive Manufacturing with Artificial Intelligence: A Review of Current and Future Trends

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F25%3A10258344" target="_blank" >RIV/61989100:27230/25:10258344 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/article/10.1007/s11831-025-10283-y" target="_blank" >https://link.springer.com/article/10.1007/s11831-025-10283-y</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11831-025-10283-y" target="_blank" >10.1007/s11831-025-10283-y</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Transforming Additive Manufacturing with Artificial Intelligence: A Review of Current and Future Trends

  • Original language description

    Additive manufacturing (AM) is a dynamic manufacturing process that provides new opportunities for creating products with intricate shapes and structures. AM, often known as Three Dimensional (3D) printing, has gained significant attention due to its technological developments, and the incorporation of artificial intelligence (AI) has further transformed its environment. This work aims to present the role of AI in various AM technologies and their industrial applications, highlighting the evolution of AM from a prototyping tool to standard manufacturing technology for final products. This review discusses the different AM technologies such as powder bed fusion (PBF), binder jetting (BJT), directed energy deposition (DED), and fused deposition modelling (FDM). This paper also covers artificial intelligence applications in design, process parameter optimization, quality control, material processing, reprocessing, and recycling. The outcomes reveal that the utilization of techniques like data acquisition coupled with Machine Learning (ML) algorithms is a foundational element bridging AM and AI. In addition, this review also addresses current challenges related to AI&apos;s role in advancing the evolution of AM technology while discussing potential areas for future research. © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2025.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20301 - Mechanical engineering

Result continuities

  • Project

  • Continuities

    O - Projekt operacniho programu

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Archives of Computational Methods in Engineering

  • ISSN

    1134-3060

  • e-ISSN

  • Volume of the periodical

    2025

  • Issue of the periodical within the volume

    Not specified

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    32

  • Pages from-to

    "not paged"

  • UT code for WoS article

    001457040800001

  • EID of the result in the Scopus database

    2-s2.0-105001646402