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https://hdl.handle.net/10356/141762
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Haridas, Aswin | en_US |
dc.contributor.author | Matham, Vadakke Murukeshan | en_US |
dc.contributor.author | Crivoi, Alexandru | en_US |
dc.contributor.author | Patinharekandy, Prabhathan | en_US |
dc.contributor.author | Jen, Tan Ming | en_US |
dc.contributor.author | Chan, Kelvin | en_US |
dc.date.accessioned | 2020-06-10T08:16:24Z | - |
dc.date.available | 2020-06-10T08:16:24Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | 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 | en_US |
dc.identifier.issn | 0143-8166 | en_US |
dc.identifier.uri | https://hdl.handle.net/10356/141762 | - |
dc.description.abstract | 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). | en_US |
dc.description.sponsorship | Economic Development Board (EDB) | en_US |
dc.description.sponsorship | National Research Foundation (NRF) | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Optics and Lasers in Engineering | en_US |
dc.rights | © 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. | en_US |
dc.subject | Engineering::Mechanical engineering | en_US |
dc.title | Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope | en_US |
dc.type | Journal Article | en |
dc.contributor.school | School of Mechanical and Aerospace Engineering | en_US |
dc.contributor.organization | Rolls-Royce @ NTU Corporate Laboratory | en_US |
dc.identifier.doi | 10.1016/j.optlaseng.2018.05.026 | - |
dc.description.version | Accepted version | en_US |
dc.identifier.scopus | 2-s2.0-85049333122 | - |
dc.identifier.volume | 110 | en_US |
dc.identifier.spage | 262 | en_US |
dc.identifier.epage | 271 | en_US |
dc.subject.keywords | Surface Roughness | en_US |
dc.subject.keywords | White Light Imaging | en_US |
dc.description.acknowledgement | 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. | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | MAE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
OLE Special Issue Article_Aswin_2018(1).pdf | 2.59 MB | Adobe PDF | View/Open |
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