Multi-objective optimization of surface roughness, dimensional errors and density in FFF 3D-printed glass fiber-reinforced PP parts via adaptive neuro-fuzzy inference modeling
This paper aims to investigate the effect of FFF 3D printing parameters on surface roughness, dimensional error and density of glass fibre-filled polypropylene (GF/PP) parts, which is a promising material to be used to obtain surgical models for bones, due to its high thermal and mechanical properti...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/441266 |
| Acceso en línea: | https://hdl.handle.net/2117/441266 https://dx.doi.org/10.1108/RPJ-11-2024-0485 |
| Access Level: | acceso abierto |
| Palabra clave: | Fuzzy modeling Regression ANFIS Optimization Roughness Dimensional accuracy Density Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomaterials |
| Sumario: | This paper aims to investigate the effect of FFF 3D printing parameters on surface roughness, dimensional error and density of glass fibre-filled polypropylene (GF/PP) parts, which is a promising material to be used to obtain surgical models for bones, due to its high thermal and mechanical properties. The experimental approach focuses on the manufacture of cuboid parts, measurement of surface roughness, dimensions and weight, and the use of ANFIS models to analyse the influence of 3D printing parameters such as printing temperature, print speed, nozzle diameter and layer height on the responses. Multi-objective optimization by means of the desirability function is then applied to obtain optimal parameters for the 3D printing parameters. The research shows the optimal values for the 3D printing parameters that are recommended in order to simultaneously minimize roughness, dimensional error and to maximize density. Specifically, a low temperature of 230 ºC, a medium print speed of 20 mm/s, a high nozzle diameter of 0.8 mm and a low layer height of 0.1 mm were found to be optimal. This present study will help select appropriate 3D printing parameters when printing surgical models in glass fibre-filled PP materials, which have recently become commercially available in FFF processes and, thus, have been scarcely studied in the literature for their use in surgical models. |
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