Fecha
2025-05-24
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Derechos de acceso
info:eu-repo/semantics/openAccess
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Elsevier
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Resumen
The emergence of Additive Manufacturing (AM) provides new horizons for innovation and optimization of designs. However, the limited knowledge of Design for Additive Manufacturing (DfAM) and the constraints imposed by conventional DfAM frameworks are hindering the potential of AM.
The scope of recent studies, focused on algorithmic approaches, is limited to certain aspects of the problem and does not offer a comprehensive solution to generate efficient custom designs. To overcome these limitations, the role of interdisciplinary and transversal DfAM methodologies is essential.
This work presents a DfAM methodology based on computational design with a continuous dataflow for the integration of all the design phases of a knowledge-based DfAM framework in a single algorithm, from initial design stages to machine code generation, what fully exploits the potential of additive technologies in customized products. This facilitates the integration of key data relationships and connections, promoting the development of intelligent and efficient open systems.
Firstly, a bibliographic review on actual knowledge-based DfAM framework is exposed. Then, the proposed methodology is detailed and discussed. Furthermore, its potential applied to customized parts with specific mechanical requirements is validated through a splint design case study. Finally, the proposed methodology advantages and limitations are discussed.
Descripción
The registered version of this article, first published in “Results in Engineering, 27 (2025); 1-30", is available online at the publisher's website: https://doi.org/10.1016/j.rineng.2025.105480
La versión registrada de este artículo, publicado por primera vez en “Results in Engineering, 27 (2025); 1-30", está disponible en línea en el sitio web del editor: https://doi.org/10.1016/j.rineng.2025.105480
Experimental data and simulation results that support the findings of this study are available in e-ciencia Datos with the identifier https://doi.org/10.21950/GKWIBY. Supplementary information is available from the corresponding author upon reasonable request
La versión registrada de este artículo, publicado por primera vez en “Results in Engineering, 27 (2025); 1-30", está disponible en línea en el sitio web del editor: https://doi.org/10.1016/j.rineng.2025.105480
Experimental data and simulation results that support the findings of this study are available in e-ciencia Datos with the identifier https://doi.org/10.21950/GKWIBY. Supplementary information is available from the corresponding author upon reasonable request
Categorías UNESCO
Palabras clave
Additive manufacturing, Design for additive manufacturing, Computational design, Optimization, Mass customization, Personalization
Citación
Amabel García-Domínguez , Juan Claver, Ana M. Camacho, Miguel A. Sebastián; Computational design methodology for additive manufacturing to enhance customised products and process management efficiency; Results in Engineering, 27 (2025); 1-30
Centro
E.T.S. de Ingenieros Industriales
Departamento
Ingeniería de Construcción y Fabricación