Central composite disigns for optimization of the energy factor in 3D printing
This study proposes an optimization strategy to analyze the trade-off between the conflicting objectives of minimizing energy use in 3D printing by fused deposition modeling. The motivation for this work is the need to optimize natural resources, finite in nature, in a more competitive industrial re...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | Brasil |
| Institución: | Sindicato das Secretárias do Estado de São Paulo (SINSESP) |
| Repositorio: | GeSec |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs2.revistagesec.org.br:article/3000 |
| Acceso en línea: | https://ojs.revistagesec.org.br/secretariado/article/view/3000 |
| Access Level: | acceso abierto |
| Palabra clave: | Central Composite Design (CCD) Fused Deposition Modeling (FDM). Response Surface Modeling (SRM) Optimization 3D printing |
| Sumario: | This study proposes an optimization strategy to analyze the trade-off between the conflicting objectives of minimizing energy use in 3D printing by fused deposition modeling. The motivation for this work is the need to optimize natural resources, finite in nature, in a more competitive industrial reality and increasingly focused on sustainability, another important point is that energy savings generate improvement in consumption raising organizational profit. The methodologies used were a brief review of the literature and response surface methodology in a CCD experiment. The modeling of the specimen took place through the CAD Fusion 360 software, its development began with the creation of a rectangular 2D sketch, obeying the parameters of 80 mm in its length and 10 mm in width, an Ender 3 printer, yellow PLA, was used following the guidelines set out in ISO 178. Objective of the research is to optimize the manufacturing process using fused deposition modeling, reducing energy consumption (kwh). A complete factorial design was used , as factors: the printing speed (X1), the printing density (X2), layer height (X3) and the layer width (X4), as a response of the experiment were adopted for the manufacturing process, energy (Y). The residue normality tests were performed, with a p-value of 0.170 > 0.05, showing that the data are normal, the VIF below 10 and R-sq (adj) is above 87.16%, the equation has the validated model. |
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