Optimization of orocessing parameters for 3D printed product using Taguchi method and desirability function analysis
| dc.contributor.author | Yasmin, Farhana | |
| dc.contributor.examiningcommittee | Khoshdarregi, Matt (Mechanical Engineering) | |
| dc.contributor.examiningcommittee | Xing, Malcolm (Mechanical Engineering) | |
| dc.contributor.supervisor | Peng, Qingjin | |
| dc.date.accessioned | 2024-03-21T18:16:43Z | |
| dc.date.available | 2024-03-21T18:16:43Z | |
| dc.date.issued | 2024-02-22 | |
| dc.date.submitted | 2024-03-12T23:15:29Z | en_US |
| dc.date.submitted | 2024-03-13T18:00:50Z | en_US |
| dc.date.submitted | 2024-03-14T18:16:40Z | en_US |
| dc.degree.discipline | Mechanical Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | |
| dc.description.abstract | Additive Manufacturing (AM) or 3D printing technologies use fused layers of the material to build the cross-sectional geometry of the product. As variable processing parameters have an impact on product quality, it is crucial to ascertain the relationships of AM process parameters, productivity, sustainability, and structure performance. This research investigates the effect of the fused deposition modeling (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. 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 variables. The optimization of response characteristics is performed using the multi-objective optimization desirability technique. The best combinations of process parameters are obtained for the chosen response variables. | |
| dc.description.note | May 2024 | |
| dc.description.sponsorship | Mitacs , North Forge | |
| dc.identifier.uri | http://hdl.handle.net/1993/38069 | |
| dc.language.iso | eng | |
| dc.rights | open access | en_US |
| dc.subject | 3D printing | |
| dc.subject | Additive manufacturing (AM) | |
| dc.subject | Design of experiment (DOE) | |
| dc.subject | Optimization | |
| dc.subject | Taguchi method | |
| dc.subject | Desirability Function Analysis | |
| dc.title | Optimization of orocessing parameters for 3D printed product using Taguchi method and desirability function analysis | |
| dc.type | master thesis | en_US |
| local.subject.manitoba | no | |
| oaire.awardTitle | Accelerate Lab2Market | |
| project.funder.identifier | U of M: https://doi.org/10.13039/100010318 | |
| project.funder.name | University of Manitoba |