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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/9296

    Título
    Ex-ante life cycle assessment of directed energy deposition based additive manufacturing: A comparative gearbox production case study
    Autor
    Santiago Herrera, MarioUBU authority Orcid
    Igos, Elorri
    Alegre Calderón, Jesús ManuelUBU authority Orcid
    Martel Martín, SoniaUBU authority Orcid
    Barros García, RocíoUBU authority Orcid
    Publicado en
    Sustainable Materials and Technologies. 2024, V. 39, e00819
    Editorial
    Elsevier
    Fecha de publicación
    2024-04
    ISSN
    2214-9937
    DOI
    10.1016/j.susmat.2023.e00819
    Abstract
    As new technologies emerge is necessary to assess if they can actually contribute to sustainable improvement of industrial processes. Life Cycle Assessment (LCA) is a valuable tool to determine environmental impacts and compare systems. However, this comparison raises challenges when they have different maturity. This paper performs ex-ante LCA of an additive manufacturing (AM) technology, based on a step-wise approach built with parametrized modelling, allowing fair comparison with its conventional counterpart, for the study case of a gearbox component. Results show that AM technology generates higher impacts than conventional manufacturing (CM) casting process, using baseline values. These impacts can be reduced by 94% with best operating performances from literature, with emissions from 4520 to 264 kg CO2 eq./kg piece, and non-significant difference with CM (demonstrated by Monte Carlo sampling). A 58% weight reduction is necessary for the AM process to improves its environmental sustainability. This research provides eco-design recommendations supporting decision making for further development of new technology.
    Palabras clave
    Life cycle assessment
    Scale-up
    Ex-ante LCA
    Additive manufacturing
    Emerging technologies
    Eco-desing
    Materia
    Ingeniería mecánica
    Mechanical engineering
    URI
    http://hdl.handle.net/10259/9296
    Versión del editor
    https://doi.org/10.1016/j.susmat.2023.e00819
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