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Title: Effect of cut-off, evaluation length, and measurement area in profile and areal surface texture characterization of as-built metal additive manufactured components
Authors: Nagalingam, Arun Prasanth
Vohra, Moiz Sabbir
Kapur, Pulkit
Yeo, Swee Hock
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: Nagalingam, A. P., Vohra, M. S., Kapur, P. & Yeo, S. H. (2021). Effect of cut-off, evaluation length, and measurement area in profile and areal surface texture characterization of as-built metal additive manufactured components. Applied Sciences, 11(11), 5089-.
Journal: Applied Sciences
Abstract: Surface texture characterization of components built using additive manufacturing (AM) remains a challenge. The presence of various asperities and random roughness distributions across a surface poses several challenges to users in selecting an appropriate cut-off wavelength (λc), evaluation length (ln), and measurement area. This paper investigates a modified framework for surface texture characterization of AM components. First, the surface asperities in an AM component were identified through scanning electron microscope (SEM) analyses. The maximum diameter (φm) of the surface asperities were determined through image processing and were used as cut-off for surface texture evaluation. Second, another set of surface texture results were extracted using standard measurement procedures per ISO 4287, 4288, 25178-1, -2, and -3. Third, the investigative measurement framework’s effectiveness and suitability were explored by comparing the results with ISO standard results. Last, the effects of using non-standard cut-off wavelength, evaluation length, and measurement area during surface texture characterization were studied, and their percentage deviations from the standard values were discussed. The key findings prove that (a) the evaluation length could be compromised instead of cut-off, (b) measurement area must be 2.5 times the maximum asperity size present in the surface, and (c) it is possible to identify, distinguish, and evaluate specific features from the AM surface by selecting appropriate filters, thereby characterizing them specifically. The investigations and the obtained results serve as valuable data for users to select appropriate measurement settings for surface texture evaluation of AM components.
ISSN: 2076-3417
DOI: 10.3390/app11115089
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Rolls-Royce@NTU Corporate Lab 
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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