Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope

The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed...

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Main Authors: Haridas, Aswin, Matham, Vadakke Murukeshan, Crivoi, Alexandru, Patinharekandy, Prabhathan, Jen, Tan Ming, Chan, Kelvin
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/141762
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1417622023-03-04T17:23:18Z Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope Haridas, Aswin Matham, Vadakke Murukeshan Crivoi, Alexandru Patinharekandy, Prabhathan Jen, Tan Ming Chan, Kelvin School of Mechanical and Aerospace Engineering Rolls-Royce @ NTU Corporate Laboratory Engineering::Mechanical engineering Surface Roughness White Light Imaging The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed structure and thus requires adequate finishing processes before implementation. Particularly, in the case of components having complex cross-sections and internal channels, none of the currently available technologies offer a solution for the measurement and certification of surface roughness parameters. In this context, this paper investigates a binary image processing technique applied to multiple white light images captured by a 0.3 mm diameter micro fiber endoscope. Further, AM sample surfaces generated by different build angles are investigated to demonstrate the advantages of the proposed technique. A surface roughness evaluation parameter is presented along with measurement results obtained using the Mitutoyo SJ400 (conventional profiler) and the Talyscan 150 (optical profiler). Economic Development Board (EDB) National Research Foundation (NRF) Accepted version This work was conducted within the Rolls-Royce@NTU Corporate Lab MRT 4.1 project with support from the National Research Foundation (NRF) Singapore under the Corp Lab@University Scheme. The authors are also grateful for the support from COLE EDB funding. 2020-06-10T08:16:24Z 2020-06-10T08:16:24Z 2018 Journal Article Haridas, A., Matham, V. M., Crivoi, A., Patinharekandy, P., Jen, T. M., & Chan, K. (2018). Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope. Optics and Lasers in Engineering, 110, 262-271. doi:10.1016/j.optlaseng.2018.05.026 0143-8166 https://hdl.handle.net/10356/141762 10.1016/j.optlaseng.2018.05.026 2-s2.0-85049333122 110 262 271 en Optics and Lasers in Engineering © 2018 Elsevier Ltd. All rights reserved. This paper was published in Optics and Lasers in Engineering and is made available with permission of Elsevier Ltd. application/pdf
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
Surface Roughness
White Light Imaging
spellingShingle Engineering::Mechanical engineering
Surface Roughness
White Light Imaging
Haridas, Aswin
Matham, Vadakke Murukeshan
Crivoi, Alexandru
Patinharekandy, Prabhathan
Jen, Tan Ming
Chan, Kelvin
Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
description The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed structure and thus requires adequate finishing processes before implementation. Particularly, in the case of components having complex cross-sections and internal channels, none of the currently available technologies offer a solution for the measurement and certification of surface roughness parameters. In this context, this paper investigates a binary image processing technique applied to multiple white light images captured by a 0.3 mm diameter micro fiber endoscope. Further, AM sample surfaces generated by different build angles are investigated to demonstrate the advantages of the proposed technique. A surface roughness evaluation parameter is presented along with measurement results obtained using the Mitutoyo SJ400 (conventional profiler) and the Talyscan 150 (optical profiler).
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Haridas, Aswin
Matham, Vadakke Murukeshan
Crivoi, Alexandru
Patinharekandy, Prabhathan
Jen, Tan Ming
Chan, Kelvin
format Article
author Haridas, Aswin
Matham, Vadakke Murukeshan
Crivoi, Alexandru
Patinharekandy, Prabhathan
Jen, Tan Ming
Chan, Kelvin
author_sort Haridas, Aswin
title Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
title_short Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
title_full Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
title_fullStr Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
title_full_unstemmed Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
title_sort surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
publishDate 2020
url https://hdl.handle.net/10356/141762
_version_ 1759855678218829824