Optimization of Processing Parameters for 3D Printed Product Using Taguchi Method

被引：0

作者：

Yasmin F. ^{[1
]}

Khan M. ^{[1
]}

Peng Q. ^{[1
]}

机构：

[1] University of Manitoba, Canada

来源：

Computer-Aided Design and Applications | 2024年 / 21卷 / 02期

关键词：

3D printing; Additive manufacturing (AM); Analysis of variance (ANOVA); Design of experiment (DOE); Fused deposition modeling (FDM); Mechanical attributes; Optimization; Sustainability; Taguchi method;

D O I：

10.14733/cadaps.2024.281-300

中图分类号：

学科分类号：

摘要：

Additive Manufacturing (AM) or 3D printing techniques use fused layers of the material to build cross sectional geometry of product. As variable processing parameters have an impact on the product quality, it is crucial to ascertain relationships of AM process parameters, productivity, sustainability, and structure performance. This study investigates the effect of the fused deposition modelling (FDM) process parameters on the response variables including mechanical attributes, energy consumption, material consumption and manufacturing time of the 3D printed product. Experiments are conducted for the FDM variable parameters of the infill pattern, infill density, layer height, printing speed, printing temperature and wall thickness. The design of the experiment approach is used to determine the best combination of the chosen parameters. A L18 orthogonal design method is employed to collect the testing data. Taguchi and analysis of variance methods are applied in the data analysis of variable FDM parameter settings. The research finds different effects on the response variable by the layer height. The wall thickness has the least impact on all the response variables. © 2024 CAD Solutions, LLC.

引用

页码：281 / 300

页数：19

共 35 条

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