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Development of Methodology for Characterization of Surface Roughness of Solid Metallic Surfaces Using Oil Slippage Method Cover

Development of Methodology for Characterization of Surface Roughness of Solid Metallic Surfaces Using Oil Slippage Method

Open Access
|Aug 2021

Abstract

The study employed the phenomenon of friction between liquid droplets and solid metallic surfaces in surface roughness analysis of engineering materials. Five samples of mild steel plate were prepared to different degrees of surface roughness by facing operation. The sample surfaces were analysed to determine the roughness parameters (mean roughness, root mean square roughness, roughness skewness, and roughness kurtosis) and friction coefficient of the surfaces. Oil droplet sliding velocity was determined using the oil slippage test. The friction coefficient of the surfaces increased with increasing roughness parameter which varied from 26.334 µm at friction coefficient = 0.63 to 13.153 µm at friction coefficient = 0.46. The results from oil slippage test showed that the sliding velocity of the oil drop decreased as the friction coefficient of samples increased. At an inclination angle of 30°, sliding velocity varied from 0.51 cm/s at friction coefficient = 0.63 to 0.92 cm/s at friction coefficient = 0.46. Some of the samples exhibited a deviation in the trend of relationship between friction coefficient and sliding velocity which resulted from the variation in peak height of roughness between the sample surfaces. Oil slippage method predicts the surface behaviours of materials based on their surface parameters.

DOI: https://doi.org/10.2478/lpts-2021-0032 | Journal eISSN: 2255-8896 | Journal ISSN: 0868-8257
Language: English
Page range: 43 - 54
Published on: Aug 10, 2021
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2021 I. O. Ohijeagbon, A. A. Adeleke, P. P. Ikubanni, T. A. Orhadahwe, G. E. Adebayo, A. S. Adekunle, A. O. Omotosho, published by Institute of Physical Energetics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.