Correlation of Surface Roping with Through-Thickness Microtextures in an AA6xxx Sheet

Abstract

Strain-induced surface roughness was quantitatively correlated with microtexture spatial distributions from the surface to the midthickness of a strongly roping AA6016 sheet. The microtexture variations through the sheet were measured by acquiring a series of large area electron backscatter diffraction (EBSD) scans at intervals of about the grain size. The orientations of the different layers were translated into out-of-plane strains using a crystal plasticity model for comparison with the surface roping. The spatial distributions (particularly the characteristic wavelengths) of the microtexture layers were determined by areal auto-correlation functions, and quantitatively compared to the surface appearance by correlation coefficients. The results show that texture banding of Cube/Goss components along the rolling direction is present from the surface to midthickness but with significant variations from one grain layer to another. The wavelength correlation coefficient exhibits a maximum at about 55 lm, or 2 grain thicknesses, below the surface. It is shown that the spatial distribution of Cube/Goss components of the first three or four surface grain layers plays an important role in strong roping of AA6016 sheets.

Quantification of roping in aluminium sheet alloys for car body applications by combining 3D surface measurements with Fourier analysis

“…This roughly corresponds to one third of the surface area on stoned samples analysed in Ref. [17,19]. A stitching of a triple measurement with the present equipment, to cover a comparable sample size has shown that the resulting ORG values lie within the range of multiple measurements on the same sample (Fig.…”

“…Guillotin et al [17,19] introduced their method based on the evaluation of the area power spectral density function (APSD) based on data of the sample surface received from images of stoned surfaces. The large-scale morphological information of the images of stoned surfaces appeared to the authors to be more pertinent than a detailed description of the surface roughness by means of a laser-scanning confocal microscope.…”

“…Therefore, the greyscale data of the corrected 3D surface profiles are transformed into Fourier space by means of a discrete fast Fourier transformation, FFT, which is basically a representation within frequency space. For a quantification of the degree of roping the corrected data set is then analysed by the use of the integrated intensities of the amplitudes spectrum of the FFT, in the style of the work by Guillotin et al [17,19]. Figure 2b shows the roping surface of Fig.…”

Breakup of texture alignment and reduction of roping in AA6111 aluminium alloy

“…The alignment of cube and Goss is actually a threedimensional (3D) phenomenon in Al-Si-Mg-(Cu) automotive alloys [10][11][12][13][14]. In previous work, the 3D texture in an AA6111 T4 sheet with intensive roping was determined from the sheet surface to 1/3 of thickness by serial sectioning and electron backscatter diffraction (EBSD) mapping [10].…”

Characterization of Roping on AA6xxx Alloy Sheet by Numerical Analysis for Surface Topography

“…Since the roping level can be detected not by roughness height, but the regularity of the stripe pattern, it is difficult to represent the roping by a traditional roughness parameter such as Ra. Guillotin et al found that the frequency method is effective to quantify roping [2,3], which was evaluated by separating the roughness pattern to isotropic and unidirectional patterns using the pictures of the roping surface after deforming and stoning. The ratio of two pattern magnitudes gives roping grade quantitatively.…”