Effect of Surface Roughness Parameters and Surface Texture for Reduced Friction

2014 ◽  
Vol 695 ◽  
pp. 572-575
Author(s):  
Samion Syahrullail ◽  
Noorawzi Nuraliza
Keyword(s):  
Surface Roughness ◽  
Friction And Wear ◽  
Test Results ◽  
Textured Surfaces ◽  
Roughness Parameters ◽  
Contact Conditions ◽  
Surface Roughness Parameters ◽  
Roughness Analysis ◽  
Pin On Disk ◽  
Effect Of Surface

The aim of the present research was to investigate the possibility of contact surfaces with reduced friction using surface roughness analysis. For this purpose, various aluminum pin samples with different lubricant using different sliding speed values were prepared. To evaluate influence of roughness parameters on friction and wear, lubricated pin-on-disk tests were carried out under different speed contact conditions. Test results show that surfaces with high values surface roughness results in reduced friction. To investigate the effect of surface topography on surface roughness parameters and consequently on friction, real roughness profiles were virtually altered to achieve virtually textured surfaces.

Modeling of Surface Topography for Reduced Friction

2008 ◽  
Author(s):  
Marko Sedlacˇek ◽  
Bojan Podgornik ◽  
Jozˇe Vizˇintin
Keyword(s):  
Surface Roughness ◽  
Surface Topography ◽  
Surface Texturing ◽  
Test Results ◽  
Textured Surfaces ◽  
Roughness Parameters ◽  
Contact Conditions ◽  
Surface Roughness Parameters ◽  
Pin On Disc ◽  
Texture Size

The aim of the present research was to investigate surface topography in terms of different surface roughness parameters and to correlate surface topography change to friction of contact surfaces. For this purpose, different 100Cr6 plate samples with different surface topography were prepared. Using different grades and combinations of grinding and polishing samples with similar Ra values, but different Rku and Rsk values were obtained. To evaluate influence of roughness parameters on friction and wear, dry and lubricated pin-on-disc tests were carried out under different contact conditions. Test results indicate that high Rku and negative Rsk values lead to decrease in friction. To investigate the effect of surface texturing on surface roughness parameters, real roughness profiles were virtually altered to achieve virtually textured surfaces. Using NIST SMATS softgauge for calculation of surface roughness parameters, virtually altered roughness profiles were investigated in terms of texture size, shape and spacing, and their influence on surface roughness parameters, especially on skewness and kurtosis. Lower diameter, higher spacing and wedge-shaped dimples reflect in higher Rku and more negative Rsk parameters.

Planning surface texturing for reduced friction in lubricated sliding using surface roughness parameters skewness and kurtosis

2012 ◽  
Vol 226 (8) ◽  
pp. 661-667 ◽  
Author(s):  
M Sedlaček ◽  
B Podgornik ◽  
J Vižintin
Keyword(s):  
Surface Roughness ◽  
Tribological Properties ◽  
Surface Texturing ◽  
Roughness Parameters ◽  
Contact Conditions ◽  
Surface Roughness Parameters ◽  
Micro Channels ◽  
Contact Surfaces ◽  
Skewness And Kurtosis ◽  
Lubricated Sliding

The aim of this research was to confirm skewness and kurtosis parameters as two main roughness parameters which describe tribological properties of contact surfaces, especially pointing out their application in surface texturing. Based on our previous virtual texturing findings, steel samples were laser textured in a manner to achieve micro-channels with different spacing and width of the channels. Lubricated tests under different contact conditions were done to evaluate their influence on friction. It was confirmed that higher Sku and more negative Ssk can be used for planning surface texturing.

scholarly journals Artificial neural network tools for predicting the functional response of ultrafast laser textured/structured surfaces

2022 ◽  
Author(s):  
Luca Baronti ◽  
Aleksandra Michalek ◽  
Marco Castellani ◽  
Pavel Penchev ◽  
Tian Long See ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Functional Response ◽  
Laser Processing ◽  
Ultrafast Laser ◽  
Generation Process ◽  
Textured Surfaces ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Artificial Neural ◽  
Areal Surface

AbstractArtificial Neural Networks (ANNs) are well-established knowledge acquisition systems with proven capacity for learning and generalisation. Therefore, ANNs are widely applied to solve engineering problems and are often used in laser-based manufacturing applications. There are different pattern recognition and control problems where ANNs can be effectively applied, and one of them is laser structuring/texturing for surface functionalisation, e.g. in generating Laser-Induced Periodic Surface Structures (LIPSS). They are a particular type of sub-micron structures that are very sensitive to changes in laser processing conditions due to processing disturbances like varying Focal Offset Distance (FOD) and/or Beam Incident Angle (BIA) during the laser processing of 3D surfaces. As a result, the functional response of LIPSS-treated surfaces might be affected, too, and typically needs to be analysed with time-consuming experimental tests. Also, there is a lack of sufficient process monitoring and quality control tools available for LIPSS-treated surfaces that could identify processing patterns and interdependences. These tools are needed to determine whether the LIPSS generation process is in control and consequently whether the surface’s functional performance is still retained. In this research, an ANN-based approach is proposed for predicting the functional response of ultrafast laser structured/textured surfaces. It was demonstrated that the processing disturbances affecting the LIPSS treatments can be classified, and then, the surface response, namely wettability, of processed surfaces can be predicted with a very high accuracy using the developed ANN tools for pre- and post-processing of LIPSS topography data, i.e. their areal surface roughness parameters. A Generative Adversarial Network (GAN) was applied as a pre-processing tool to significantly reduce the number of required experimental data. The number of areal surface roughness parameters needed to fully characterise the functional response of a surface was minimised using a combination of feature selection methods. Based on statistical analysis and evolutionary optimisation, these methods narrowed down the initial set of 21 elements to a group of 10 and 6 elements, according to redundancy and relevance criteria, respectively. The validation of ANN tools, using the salient surface parameters, yielded accuracy close to 85% when applied for identification of processing disturbances, while the wettability was predicted within an r.m.s. error of 11 degrees, equivalent to the static water contact angle (CA) measurement uncertainty.

scholarly journals Analysis of selected surface roughness parameters the AW 6082 T6 aluminum alloy after turning process

Mechanik ◽  
2018 ◽  
Vol 91 (8-9) ◽  
pp. 730-732 ◽  
Author(s):  
Mariusz Kłonica
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Control System ◽  
Roughness Parameters ◽  
Turning Process ◽  
Measuring Device ◽  
Surface Roughness Parameters ◽  
Spherical Surfaces ◽  
Roughness Analysis ◽  
2D And 3D

The paper presents selected research results concerning the surface roughness analysis of 2D and 3D after the turning process AW 6082 T6 aluminum alloy. The conical and spherical surfaces were analyzed. Samples made of aluminum alloy were made on a DMG MORI CTX450 numerically controlled lathe equipped with the Sinumerik 840D control system. The Hommel-Etamic T8000 RC-12-40 measuring device with a measuring radius of 2 μm was used to measure the selected surface roughness parameters. The Keyence VHX-5000 microscope was also used in the study to visualize the resulting surfaces.

Effect of surface roughness parameters on thermally sprayed PEEK coatings

2010 ◽  
Vol 204 (21-22) ◽  
pp. 3567-3572 ◽  
Author(s):  
Krishal Patel ◽  
Colin S. Doyle ◽  
Daisuke Yonekura ◽  
Bryony J. James
Keyword(s):  
Surface Roughness ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Thermally Sprayed ◽  
Effect Of Surface

Effect of Surface Roughness on Slip Resistance of Rubber

2011 ◽  
Vol 189-193 ◽  
pp. 1538-1542
Author(s):  
Li Xiao Jia ◽  
Yong Zhen Zhang ◽  
Yong Ping Niu ◽  
San Ming Du ◽  
Jian Li
Keyword(s):  
Surface Roughness ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Roughness Parameters ◽  
Test Conditions ◽  
Slip Resistance ◽  
Materials Used ◽  
Almost All ◽  
Effect Of Surface

In order to decrease accidents of slips and falls, COFs of rubber samples with different surface roughness were measured by Brungraber Mark II. And the correlation coefficients between roughness parameters and COF were calculated. The rusults have shown that the COF increases with surface roughness and the correlation coefficient between Sq and COF is highest. In general, almost all the roughness parameters used in the study have high correlation with COF. Parameters had the highest correlation with COF depends on the materials used and test conditions.

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