Literature DB >> 24038147

How to select the most relevant 3D roughness parameters of a surface.

R Deltombe1, K J Kubiak, M Bigerelle.   

Abstract

In order to conduct a comprehensive roughness analysis, around sixty 3D roughness parameters are created to describe most of the surface morphology with regard to specific functions, properties or applications. In this paper, a multiscale surface topography decomposition method is proposed with application to stainless steel (AISI 304), which is processed by rolling at different fabrication stages and by electrical discharge tool machining. Fifty-six 3D-roughness parameters defined in ISO, EUR, and ASME standards are calculated for the measured surfaces. Then, expert software "MesRug" is employed to perform statistical analysis on acquired data in order to find the most relevant parameters characterizing the effect of both processes (rolling and machining), and to determine the most appropriate scale of analysis. For the rolling process: The parameter Vmc (the Core Material Volume--defined as volume of material comprising the texture between heights corresponding to the material ratio values of p = 10% and q = 80%) computed at the scale of 3 µm is the most relevant parameter to characterize the cold rolling process. For the EDM Process, the best roughness parameter is SPD that represents the number of peaks per unit area after segmentation of a surface into motifs computed at the scale of 8 µm. © Wiley Periodicals, Inc.

Entities:  

Keywords:  3D-roughness parameters; ANOVA; Sendzimir cold rolling; bootstrap method; electrical discharge machining; statistical analysis; surface roughness

Year:  2013        PMID: 24038147     DOI: 10.1002/sca.21113

Source DB:  PubMed          Journal:  Scanning        ISSN: 0161-0457            Impact factor:   1.932


  3 in total

1.  A Tribological Comparison of Facet Joint, Sacroiliac Joint, and Knee Cartilage in the Yucatan Minipig.

Authors:  Rachel C Nordberg; M Gabriela Espinosa; Jerry C Hu; Kyriacos A Athanasiou
Journal:  Cartilage       Date:  2021-06-09       Impact factor: 3.117

2.  How to Select 2D and 3D Roughness Parameters at Their Relevant Scales by the Analysis of Covariance.

Authors:  Stephane Tchoundjeu; Maxence Bigerelle; Francois Robbe-Valloire; Tony Da Silva Botelho; Frederic Jarnias
Journal:  Materials (Basel)       Date:  2020-03-26       Impact factor: 3.623

3.  Simple Discriminatory Methodology for Wear Analysis of Cutting Tools: Impact on Work Piece Surface Morphology in Case of Differently Milled Kinetics Steel H13.

Authors:  Teresa Prado; Alejandro Pereira; Maria Fenollera; Thomas G Mathia
Journal:  Materials (Basel)       Date:  2020-01-04       Impact factor: 3.623

  3 in total

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