Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing
Additive manufacturing is seen to the next big thing as it has a major competitive advantage over the rest of other traditional manufacturing technology due to the flexibility in the design of the product and the potential cost savings due to the reduction in the amount of material used to produce a...
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2016
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sg-ntu-dr.10356-679972023-03-04T18:24:06Z Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing Ho, Vanessa Kah Hui Brian Stephen Wong School of Mechanical and Aerospace Engineering A*STAR Singapore Institute of Manufacturing Technology DRNTU::Engineering Additive manufacturing is seen to the next big thing as it has a major competitive advantage over the rest of other traditional manufacturing technology due to the flexibility in the design of the product and the potential cost savings due to the reduction in the amount of material used to produce a part. Hence, it is of upmost importance to ensure that the 3D printed part satisfy certain criteria such as porosity level. Thus, this project proposes methods to analyse the porosity of a 3D printed stainless steel specimen. The porosity of a sample is calculated by analysing CT images through MATLAB image processing functions. The results from the proposed method are then compared to that other known methods such as ultrasound and metallurgical cross sectioning in order to determine if each method would produce the similar results. After which, the results obtained from is analysed to determine the best method to evaluate the 3D printed specimen. Bachelor of Engineering (Aerospace Engineering) 2016-05-24T02:11:37Z 2016-05-24T02:11:37Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67997 en Nanyang Technological University 119 p. application/pdf |
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DRNTU::Engineering Ho, Vanessa Kah Hui Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
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Additive manufacturing is seen to the next big thing as it has a major competitive advantage over the rest of other traditional manufacturing technology due to the flexibility in the design of the product and the potential cost savings due to the reduction in the amount of material used to produce a part. Hence, it is of upmost importance to ensure that the 3D printed part satisfy certain criteria such as porosity level. Thus, this project proposes methods to analyse the porosity of a 3D printed stainless steel specimen.
The porosity of a sample is calculated by analysing CT images through MATLAB image processing functions. The results from the proposed method are then compared to that other known methods such as ultrasound and metallurgical cross sectioning in order to determine if each method would produce the similar results. After which, the results obtained from is analysed to determine the best method to evaluate the 3D printed specimen. |
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Brian Stephen Wong |
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Brian Stephen Wong Ho, Vanessa Kah Hui |
format |
Final Year Project |
author |
Ho, Vanessa Kah Hui |
author_sort |
Ho, Vanessa Kah Hui |
title |
Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
title_short |
Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
title_full |
Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
title_fullStr |
Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
title_full_unstemmed |
Investigation of X-ray computed tomography as a tool for non-destructive evaluation of components produced by 3D printing |
title_sort |
investigation of x-ray computed tomography as a tool for non-destructive evaluation of components produced by 3d printing |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/67997 |
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1759857030295715840 |