Effects of fused filament fabrication parameters on the manufacturing of 316L stainless-steel components: geometric and mechanical properties
Purpose: The extrusion-based additive manufacturing method followed by debinding and sintering steps can produce metal parts efficiently at a relatively low cost and material wastage. In this study, 316L stainless-steel metal filled filaments were used to print metal parts using the extrusion-based...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/32978 |
| Acceso en línea: | https://hdl.handle.net/10578/32978 |
| Access Level: | acceso abierto |
| Palabra clave: | Additive manufacturing Porosity Fused filament fabrication Dimensional accuracy Mechanical characterization 316L austenitic stainless-steel Process parameters |
| Sumario: | Purpose: The extrusion-based additive manufacturing method followed by debinding and sintering steps can produce metal parts efficiently at a relatively low cost and material wastage. In this study, 316L stainless-steel metal filled filaments were used to print metal parts using the extrusion-based fused filament fabrication (FFF) approach. The purpose of this study is to assess the effects of common FFF printing parameters on the geometric and mechanical performance of FFF manufactured 316L stainless-steel components. Design/methodology/approach: The microstructural characteristics of the metal filled filament, three-dimensional (3D) printed green parts and final sintered parts were analysed. In addition, the dimensional accuracy of the green parts was evaluated, as well as the hardness, tensile properties, relative density, part shrinkage and the porosity of the sintered samples. Moreover, surface quality in terms of surface roughness after sintering was assessed. Predictive models based on artificial neural networks (ANNs) were used for characterizing dimensional accuracy, shrinkage, surface roughness and density. Additionally, the response surface method based on ANNs was applied to represent the behaviour of these parameters and to identify the optimum 3D printing conditions. Findings: The effects of the FFF process parameters such as build orientation and nozzle diameter were significant. The pore distribution was strongly linked to the build orientation and printing strategy. Furthermore, porosity decreased with increased nozzle diameter, which increased mechanical performance. In contrast, lower nozzle diameters achieved lower roughness values and average deviations. Thus, it should be noted that the modification of process parameters to achieve greater geometrical accuracy weakened mechanical performance. Originality/value: Near-dense 316L austenitic stainless-steel components using FFF technology were successfully manufactured. This study provides print guidelines and further information regarding the impact of FFF process parameters on the mechanical, microstructural and geometric performance of 3D printed 316L components. |
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