Statistical Analysis of Profilometric Sampling for Roughness Parameters

2009 ◽  
pp. 58-58-13 ◽  
Author(s):  
WJ Drury ◽  
AM Gokhale
Keyword(s):  
Statistical Analysis ◽  
Roughness Parameters

scholarly journals Statistical analysis of the influence of print run on surface roughness of digital flexo printing plates’ solid tone areas

2020 ◽  
Author(s):  
Sandra Dedijer ◽  
◽  
Magdolna Pál ◽  
Ivana Tomić ◽  
Stefan Poljak ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Statistical Evaluation ◽  
Statistical Significance ◽  
Test Method ◽  
Roughness Parameters ◽  
Printing Plate ◽  
Significance Level ◽  
Surface Roughness Parameters ◽  
The Difference

In this study we have aimed to present statistical evaluation of changes in the surface roughness of the solid tone areas on CtP flexo printing plate in dependence of print run. Changes in flexo plate surface roughness is influenced by the plate-making process, printing pressure and speed, the interaction with the ink and printing substrate and by the wear of the printing plate due to long print-runs. Thus, the aim of this research was to evaluate the changes in the amplitude surface roughness parameters (Ra, Rp, Rv and Rz), between the printing plates used for different print runs. In the experiment, we have employed three sets of CtP flexo printing plates, for three colors-cyan, magenta and blue. The first set was not used for printing, the second was used to print 7 rolls of substrate and the third is used to print 11 rolls of printing substrate. The amplitude surface roughness parameters were compared by applying independentsamples t-test method using the software SPSS (Statistical Package for Social Science) with a 0.05 significance level. Statistical analysis revealed that the difference between the amplitude surface roughness parameters measured on CtP flexo printing plates are significant with a 95% confidence level, whereas the statistical significance pointed out that with the longer print runs, the difference will be strongly expressed.

scholarly journals The Condition of Ni-Cr Alloy Surface After Abrasive Blasting with Various Parameters

2019 ◽  
Vol 29 (3) ◽  
pp. 1439-1444
Author(s):  
Weronika Czepułkowska ◽  
Emilia Wołowiec-Korecka ◽  
Leszek Klimek
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
Statistical Analysis ◽  
Metal Surface ◽  
Statistical Significance ◽  
Alloy Surface ◽  
Particle Sizes ◽  
Roughness Parameters ◽  
Abrasive Particles ◽  
Abrasive Blasting

Abstract The parameters of abrasive blasting process directly affect the condition of the metal surface, changing the degree of surface roughness and wettability, depending on the size of the used particle, the pressure or type of abrasive. The aim of this study was to analyze the condition of Ni-Cr alloy surface after abrasive blasting using various process variants. The samples were blasted by Al2O3 abrasive using various particle sizes and pressures of the process. Basic and specific roughness parameters were investigated, and a surface wettability test was performed, and the percentage share of abrasive particles penetrated in the surface after abrasive blasting was also examined. The most considerable differences in the condition of the surface were observed with the change in the particle size of Al2O3. Statistical analysis confirmed the statistical significance of all these relationships.

scholarly journals Study on Fabric Surface Roughness and its Influence on Worsted Fabric Abrasion Resistance

2015 ◽  
Vol 10 (4) ◽  
pp. 155892501501000
Author(s):  
Sara Asghari Mooneghi ◽  
S. Mohammad Hosseini Varkiyani ◽  
Siamak Saharkhiz
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Abrasion Resistance ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Roughness Parameters ◽  
3D Surface Roughness ◽  
Strong Linear Correlation ◽  
Fabric Surface ◽  
2D And 3D

Surface roughness is of paramount importance in predicting tactile properties of fabrics. This study aimed at investigating surface roughness and the effect of this property on the abrasion resistance of worsted fabrics. Nine different groups of worsted fabrics were produced. The fabrics had three weave types and three areal densities. A non-contact laser based system was developed to scan the surface of the fabrics. In order to extract the surface roughness profile, a new method of data analysis was presented. Several two dimensional (2D) and three dimensional (3D) roughness parameters were introduced and calculated. Statistical analysis proved that the effect of weave type and weft density was significant on all of the 2D and 3D surface roughness parameters at a confidence range of 95%. However, the 3D parameters provided the surface roughness with just one number in comparison with the 2D ones (warp and weft directions). Therefore, the 3D parameters provided a better indication for the surface roughness which had the effect of both warp and weft directions. Results showed that there was a strong linear correlation between the abrasion resistance and the 3D roughness parameters.

scholarly journals Statistical Analysis of Surface Roughness Parameters for Weft Knitted Fabrics Measured by the Textile Surface Tester (TST)

2012 ◽  
Vol 7 (4) ◽  
pp. 155892501200700 ◽  
Author(s):  
Najeh Maâtoug ◽  
Mehdi Sahnoun ◽  
Faouzi Sakli
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Sampling Time ◽  
Structural Factors ◽  
Roughness Parameters ◽  
Knitted Fabrics ◽  
Signal Sampling ◽  
Test Conditions ◽  
Surface Roughness Parameters ◽  
Yarn Count

The present paper concerns the statistical analysis of the surface roughness evaluation of knitted fabrics by the Textile Surface Tester. The main objectives were, firstly, focused on investigating the effect of knitted fabrics structural factors and the test conditions on the surface absolute roughness, the total roughness and the standard deviation. Secondly, the relationship between sample characteristics (face, yarn count, loop length), the test conditions (the force and the slipping speed of the sensor feeler on the sample and signal sampling time), and the surface roughness parameters were analyzed and modeled through regression analysis. The combined effects of the input parameters and their two-way interactions on the test bench outputs were investigated using the analysis of variance (ANOVA). The percent contribution ratio was used to show the influence of inputs and their interactions on surface roughness parameters. The results show how much surface roughness is mainly influenced by the knits structural factors. Also, it is underlined that the applied force by the sensor feeler on the fabric has an important effect on outputs. Finally, the sensor slipping speed on the sample and the signal sampling time have no important effects on outputs. Models were developed using experimental results from a full factorial experimental design. The adjusted coefficients of determination R2adj were found to be greater than 80%.

Effects of high speed in the drilling of glass whisker-reinforced polyamide composites (PA66 GF30): statistical analysis of the roughness parameters

2010 ◽  
Vol 45 (13) ◽  
pp. 1395-1402 ◽  
Author(s):  
J. Campos Rubio ◽  
T.H. Panzera ◽  
A.M. Abrao ◽  
Paulo E. Faria ◽  
J. Paulo Davim
Keyword(s):  
Statistical Analysis ◽  
High Speed ◽  
Roughness Parameters

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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