Non-destructive measurement of surface roughness of 3D printed sample

Additive manufacturing has since gained popularity in the manufacturing industry. However, achieving high surface finishing while producing complex designs, such as those with internal features and multiple curvatures is a challenge that manufacturers might face these days. A well-established method...

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Main Author: Ong, Jun Hao
Other Authors: Fan Zheng, David
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/157918
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1579182023-03-04T20:17:03Z Non-destructive measurement of surface roughness of 3D printed sample Ong, Jun Hao Fan Zheng, David School of Mechanical and Aerospace Engineering ZFAN@ntu.edu.sg Engineering::Mechanical engineering Additive manufacturing has since gained popularity in the manufacturing industry. However, achieving high surface finishing while producing complex designs, such as those with internal features and multiple curvatures is a challenge that manufacturers might face these days. A well-established method of surface finishing known as abrasive flow machining (AFM) can be used to tackle this issue. Although AFM is an advanced technology, it is still not able to track the surface roughness of the object during the polishing process. Operators have to resort to multiple sessions of polishing which is tedious and time-consuming. Therefore, this report serves to present an online monitoring method for the internal surface roughness of metallic components through the use of a frequency-based ultrasonic testing method. The method used consists of using an auto-alignment rig with a delay line transducer attached. Along with the help of MATLAB software, the monitoring process will be automated throughout the process of surface finishing using the AFM process. The reconstructed roughness obtained from the tests will then be validated using measurements taken from a stylus profilometer. Although the results obtained were inconsistent and inaccurate due to overestimations, the proposed method was able to capture the rate at which surface roughness decreases during the polishing process. With further calibrations and adjustments made, it is possible to improve the results. Lastly, to simulate real-world scenarios, offline ultrasonic testing was done on a rounded channel sample with a curved target surface and an aluminium plate with a flat target surface for comparison. Results have shown that a transducer at a low frequency is more suitable for roughness measurements of curved target surfaces and due to the effects of curvatures, results are more susceptible to overestimations if not well-compensated. Bachelor of Engineering (Mechanical Engineering) 2022-05-25T03:54:27Z 2022-05-25T03:54:27Z 2022 Final Year Project (FYP) Ong, J. H. (2022). Non-destructive measurement of surface roughness of 3D printed sample. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157918 https://hdl.handle.net/10356/157918 en B075 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
Ong, Jun Hao
Non-destructive measurement of surface roughness of 3D printed sample
description Additive manufacturing has since gained popularity in the manufacturing industry. However, achieving high surface finishing while producing complex designs, such as those with internal features and multiple curvatures is a challenge that manufacturers might face these days. A well-established method of surface finishing known as abrasive flow machining (AFM) can be used to tackle this issue. Although AFM is an advanced technology, it is still not able to track the surface roughness of the object during the polishing process. Operators have to resort to multiple sessions of polishing which is tedious and time-consuming. Therefore, this report serves to present an online monitoring method for the internal surface roughness of metallic components through the use of a frequency-based ultrasonic testing method. The method used consists of using an auto-alignment rig with a delay line transducer attached. Along with the help of MATLAB software, the monitoring process will be automated throughout the process of surface finishing using the AFM process. The reconstructed roughness obtained from the tests will then be validated using measurements taken from a stylus profilometer. Although the results obtained were inconsistent and inaccurate due to overestimations, the proposed method was able to capture the rate at which surface roughness decreases during the polishing process. With further calibrations and adjustments made, it is possible to improve the results. Lastly, to simulate real-world scenarios, offline ultrasonic testing was done on a rounded channel sample with a curved target surface and an aluminium plate with a flat target surface for comparison. Results have shown that a transducer at a low frequency is more suitable for roughness measurements of curved target surfaces and due to the effects of curvatures, results are more susceptible to overestimations if not well-compensated.
author2 Fan Zheng, David
author_facet Fan Zheng, David
Ong, Jun Hao
format Final Year Project
author Ong, Jun Hao
author_sort Ong, Jun Hao
title Non-destructive measurement of surface roughness of 3D printed sample
title_short Non-destructive measurement of surface roughness of 3D printed sample
title_full Non-destructive measurement of surface roughness of 3D printed sample
title_fullStr Non-destructive measurement of surface roughness of 3D printed sample
title_full_unstemmed Non-destructive measurement of surface roughness of 3D printed sample
title_sort non-destructive measurement of surface roughness of 3d printed sample
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157918
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