Please use this identifier to cite or link to this item:
Title: Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope
Authors: Haridas, Aswin
Matham, Vadakke Murukeshan
Crivoi, Alexandru
Patinharekandy, Prabhathan
Jen, Tan Ming
Chan, Kelvin
Keywords: Engineering::Mechanical engineering
Issue Date: 2018
Source: 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
Journal: Optics and Lasers in Engineering
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).
ISSN: 0143-8166
DOI: 10.1016/j.optlaseng.2018.05.026
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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

Files in This Item:
File Description SizeFormat 
OLE Special Issue Article_Aswin_2018(1).pdf2.59 MBAdobe PDFView/Open

Citations 20

Updated on Jan 28, 2023

Web of ScienceTM
Citations 20

Updated on Feb 2, 2023

Page view(s)

Updated on Feb 4, 2023

Download(s) 50

Updated on Feb 4, 2023

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.