Optimization for DED processes via experiments
Directed Energy Deposition (DED) is a Additional Manufacturing (AM) method which utilizes laser to melt metal filaments or powders to form complex 3-Diamentional parts from computer models. Due to the nature of this process, there exists several fundamental problems. One such issue is the low qualit...
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sg-ntu-dr.10356-1671102023-05-27T16:51:52Z Optimization for DED processes via experiments Quek, Jun Kang Li Hua School of Mechanical and Aerospace Engineering LiHua@ntu.edu.sg Engineering::Mechanical engineering Directed Energy Deposition (DED) is a Additional Manufacturing (AM) method which utilizes laser to melt metal filaments or powders to form complex 3-Diamentional parts from computer models. Due to the nature of this process, there exists several fundamental problems. One such issue is the low quality of layers and accumulative errors in subsequent printed layers. This can lead to printed material either being too small or too big to meet required specifications and result in more post processing required. To minimize this issue, this project aims to optimize the 5 main process parameters of laser power, powder mass flow rate, scanning speed, hatch spacing ratio, and height incremental ratio. The geometrical characteristics of layer height and surface waviness are investigated to obtain an optimized set of parameters for use on multilayer multi-thread parts. Design of Experiments (DOE) setup based on Response Surface Methodology (RSM) was employed to determine the optimal set of process parameters. Findings from this paper suggest that the hatch spacing ratio is of significant importance in the determining of surface waviness. In addition, findings also suggest that the powder mass flow rate is a key variable to control to minimize the layer height deviation, which leads to reducing the accumulative errors in subsequent deposited layers. An optimized set of process parameters is also obtained. Finally, recommendations for future works are also proposed. Bachelor of Engineering (Mechanical Engineering) 2023-05-23T05:05:16Z 2023-05-23T05:05:16Z 2023 Final Year Project (FYP) Quek, J. K. (2023). Optimization for DED processes via experiments. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167110 https://hdl.handle.net/10356/167110 en B121 application/pdf Nanyang Technological University |
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Engineering::Mechanical engineering Quek, Jun Kang Optimization for DED processes via experiments |
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Directed Energy Deposition (DED) is a Additional Manufacturing (AM) method which utilizes laser to melt metal filaments or powders to form complex 3-Diamentional parts from computer models. Due to the nature of this process, there exists several fundamental problems. One such issue is the low quality of layers and accumulative errors in subsequent printed layers. This can lead to printed material either being too small or too big to meet required specifications and result in more post processing required. To minimize this issue, this project aims to optimize the 5 main process parameters of laser power, powder mass flow rate, scanning speed, hatch spacing ratio, and height incremental ratio. The geometrical characteristics of layer height and surface waviness are investigated to obtain an optimized set of parameters for use on multilayer multi-thread parts. Design of Experiments (DOE) setup based on Response Surface Methodology (RSM) was employed to determine the optimal set of process parameters. Findings from this paper suggest that the hatch spacing ratio is of significant importance in the determining of surface waviness. In addition, findings also suggest that the powder mass flow rate is a key variable to control to minimize the layer height deviation, which leads to reducing the accumulative errors in subsequent deposited layers. An optimized set of process parameters is also obtained. Finally, recommendations for future works are also proposed. |
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Li Hua |
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Li Hua Quek, Jun Kang |
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Final Year Project |
author |
Quek, Jun Kang |
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Quek, Jun Kang |
title |
Optimization for DED processes via experiments |
title_short |
Optimization for DED processes via experiments |
title_full |
Optimization for DED processes via experiments |
title_fullStr |
Optimization for DED processes via experiments |
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Optimization for DED processes via experiments |
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optimization for ded processes via experiments |
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Nanyang Technological University |
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2023 |
url |
https://hdl.handle.net/10356/167110 |
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