Additive manufacturing: DED process parameters optimisation via simulation

With the increasing popularity of Additive Manufacturing in recent years, there has been a growing focus on optimising its processes to leverage its numerous benefits over traditional subtractive manufacturing. Among the various additive manufacturing techniques, Directed Energy Deposition (DE...

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Main Author: Quek, Derek Zong Xun
Other Authors: Li Hua
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/167435
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1674352023-06-03T16:49:54Z Additive manufacturing: DED process parameters optimisation via simulation Quek, Derek Zong Xun Li Hua School of Mechanical and Aerospace Engineering LiHua@ntu.edu.sg Engineering::Mechanical engineering With the increasing popularity of Additive Manufacturing in recent years, there has been a growing focus on optimising its processes to leverage its numerous benefits over traditional subtractive manufacturing. Among the various additive manufacturing techniques, Directed Energy Deposition (DED) is the most prevalent, and extensive research is being carried out to optimise its operational parameters towards achieving multi-objective optimisation, thereby revolutionising the industry. This Final Year Project (FYP) aims to investigate these input parameters, with a specific focus revolving around the convergence (focal point) of the powder flow. Python Programming was integrated to standardise manual processes and remove variabilities, enhancing accuracy. ANSYS simulation was employed to replicate a real life DED nozzle, with emphasis placed on improving meshing techniques to better visualize flow behaviour. Results examination suggested that these new implementations are on the right path, as evidenced by the similarity of trends to experimental results. This offers promising new avenues for further refinement and improvements, which will help to narrow the gap in optimisation studies and advance the understanding of DED processes. Bachelor of Engineering (Mechanical Engineering) 2023-05-28T12:27:16Z 2023-05-28T12:27:16Z 2023 Final Year Project (FYP) Quek, D. Z. X. (2023). Additive manufacturing: DED process parameters optimisation via simulation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167435 https://hdl.handle.net/10356/167435 en B119 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Quek, Derek Zong Xun
Additive manufacturing: DED process parameters optimisation via simulation
description With the increasing popularity of Additive Manufacturing in recent years, there has been a growing focus on optimising its processes to leverage its numerous benefits over traditional subtractive manufacturing. Among the various additive manufacturing techniques, Directed Energy Deposition (DED) is the most prevalent, and extensive research is being carried out to optimise its operational parameters towards achieving multi-objective optimisation, thereby revolutionising the industry. This Final Year Project (FYP) aims to investigate these input parameters, with a specific focus revolving around the convergence (focal point) of the powder flow. Python Programming was integrated to standardise manual processes and remove variabilities, enhancing accuracy. ANSYS simulation was employed to replicate a real life DED nozzle, with emphasis placed on improving meshing techniques to better visualize flow behaviour. Results examination suggested that these new implementations are on the right path, as evidenced by the similarity of trends to experimental results. This offers promising new avenues for further refinement and improvements, which will help to narrow the gap in optimisation studies and advance the understanding of DED processes.
author2 Li Hua
author_facet Li Hua
Quek, Derek Zong Xun
format Final Year Project
author Quek, Derek Zong Xun
author_sort Quek, Derek Zong Xun
title Additive manufacturing: DED process parameters optimisation via simulation
title_short Additive manufacturing: DED process parameters optimisation via simulation
title_full Additive manufacturing: DED process parameters optimisation via simulation
title_fullStr Additive manufacturing: DED process parameters optimisation via simulation
title_full_unstemmed Additive manufacturing: DED process parameters optimisation via simulation
title_sort additive manufacturing: ded process parameters optimisation via simulation
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167435
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