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Recycled powder age estimation based on morphology evolution for the LPBF-M process

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Abstract

Metallic powder alloys for additive manufacturing (AM) are required to have a certain particle size and shape distribution in different processes such as laser powder bed fusion for metallic alloys (LPBF-M). For reasons of sustainability and cost-effectiveness, it is common to recycle powder that was not melted in the build construction process. As usual in a LPBF-M process, the metal powder undergoes a heuristical designed sieving and blending procedure to maintain a certain particle distribution. However, keeping track of the powder’s mean age during each building cycle can be obscure or laborious. To overcome this challenge, the authors of this research propose a theoretical model and an experimental methodology to track the powder morphology evolution with respect to a specific number of building cycles and the sieved and solidified amount of powder Such morphological investigation was carried out through a scanning electron microscope, analyzing the morphological evolution of nickel-chromium alloy metal (Inconel 718) powder. The powder analysis gives a close fit of its mean age to the span of the retained particle solidity measurements and the evolution of the mean major diameter. Recycling and thereby modifying the ageing rate of the powder, under monitoring the morphologic evolution of the particles, could be considered as a key criterion for a more effective powder usage lifetime. The findings from this methodology give insight on a predictive model for aging rate, capable of retrieving information about the effective powder’s lifetime, impacting positively in the organization and storage of metal powders for AM.

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Data Availability

The data and materials of this article are obtained in the experiment and are real data. All data and materials used to produce the results in this article can be obtained upon request from the corresponding author.

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Funding

This work was supported by the CONACyT grants LN315910, LN314934, LN299129 and UNAM DGAPA PAPIIT project IA102922 and IT102423.

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Authors and Affiliations

  1. Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México (UNAM), Circuito Exterior S/N, Ciudad Universitaria, Coyoacán, 04510, Mexico City, Mexico

    Leopoldo Ruiz-Huerta, Verena M. Moock & Alberto Caballero-Ruiz

  2. National Laboratory for Additive and Digital Manufacturing (MADiT), Coyoacán, Mexico

    Leopoldo Ruiz-Huerta, Verena M. Moock, Nicolás A. Ulloa-Castillo, Emmanuel Segura-Cárdenas, Alan Borbolla-Vázquez, Alex Elías-Zúñiga & Alberto Caballero-Ruiz

  3. Center for Innovation in Digital Technologies, Department of Mechanical Engineering and Advanced Materials, School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey, 64849, Nuevo León, Mexico

    Nicolás A. Ulloa-Castillo

  4. School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey, 64849, Nuevo León, Mexico

    Emmanuel Segura-Cárdenas

  5. Programa de Maestría y Doctorado en Ingeniería, Universidad Nacional Autónoma de México (UNAM), Building S. Bernardo Quintana Arrioja, 1st floor, Ciudad Universitaria, Coyoacán, 04510, Mexico City, Mexico

    Alan Borbolla-Vázquez

  6. Department of Mechanical Engineering and Advanced Materials, Institute of Advanced Materials for Sustainable Manufacturing, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey, 64849, Nuevo León, Mexico

    Alex Elías-Zúñiga

Authors
  1. Leopoldo Ruiz-Huerta
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  2. Verena M. Moock
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  7. Alberto Caballero-Ruiz
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Correspondence to Leopoldo Ruiz-Huerta.

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Author contribution

All authors contributed to the writing, editing and reviewing process. Original proposal: L. R-H. Concept: L. R-H and A. B-V.. Design: L. R-H; A. B-V, V. M, N. U-C, E. S-C, A. E and A C-R. Experiments: N. U-C and E. S-C. Data analysis: V. M., N. U-C and L R-H. Funding: L R-H, A. E. and V. M.

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Ruiz-Huerta, L., Moock, V.M., Ulloa-Castillo, N.A. et al. Recycled powder age estimation based on morphology evolution for the LPBF-M process. Int J Adv Manuf Technol 124, 383–396 (2023). https://doi.org/10.1007/s00170-022-10429-3

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