Milled die steel surface roughness correlation with steel sheet friction

Berglund, Johan; Brown, Christopher; Rosén, Bengt-Göran; Bay, Niels

doi:10.1016/j.cirp.2010.03.140

Cited by 56 publications

(28 citation statements)

References 9 publications

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“…This result indicates that an optimal combination of pre-processing and subsequent polishing exists, yielding functional surfaces with superior tribological performance. This finding is in good agreement with results earlier obtained by other researchers conducting similar tests on the influence of topography of tool surface [6] and work piece surface [7].…”

Section: Resultssupporting

confidence: 83%

Manufacture of functional surfaces through combined application of tool manufacturing processes and Robot Assisted Polishing

Eriksen

Arentoft

Grønbæk³

et al. 2012

CIRP Annals

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The tool surface topography is often a key parameter in the tribological performance of modern metal forming tools. A new generation of multifunctional surfaces is achieved by combination of conventional tool manufacturing processes with a novel robot assisted polishing process. This novel surface texturing method allows for a large degree of freedom in specifying surface characteristics and facilitates a high degree of reproducibility between samples surfaces. A series of strip reduction tests, equivalent to a metal forming ironing process, are conducted to benchmark the tribological performance of 15 generated tool surfaces.

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Section: Resultssupporting

confidence: 83%

Manufacture of functional surfaces through combined application of tool manufacturing processes and Robot Assisted Polishing

Eriksen

Arentoft

Grønbæk³

et al. 2012

CIRP Annals

Self Cite

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“…This multi-parameter representation of surface roughness has been reported in various works and some efforts have been put previously to develop a method for selecting relevant parameters (Scott et al 2005, Narayan et al 2006, Jordan et al 2006, Berglund et al 2010, Bigerelle et al 2005b). …”

Section: 4mentioning

confidence: 99%

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

2013

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This is the pre-peer reviewed version of the following article: Deltombe R., Kubiak K.J., Bigerelle M, How to select the most relevant 3D roughness parameters of a surface (2011) Summary: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 3Droughness 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 mm 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.

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“…If this separation in the three ranges of variation is sufficient to correlate with the analysed behaviour in some simple cases, Raja and Radhakrishan [19] show that both the need for manufacturers to control their surface finishing process and the need in functional analysis require finer frequency analysis on the entire range of wavelengths available from the measurements. The so-called multi-scale and/or multi-resolution methods include the ability to address this issue [20,21], application examples to abrasion and friction are detailed respectively in [22] and [23].…”

Section: Methods: Multiscale Filtering and Analysismentioning

confidence: 99%