Anisotropy can influence surface function and can be an indication of processing. These influences and indications include friction, wetting, and microwear. This article studies two methods for multiscale quantification and visualization of anisotropy. One uses multiscale curvature tensor analysis and shows anisotropy in horizontal coordinates i.e., topocentric. The other uses multiple bandpass filters (also known as sliding bandpass filters) applied prior to calculating anisotropy parameters, texture aspect ratios (Str) and texture directions (Std), showing anisotropy in horizontal directions only. Topographies were studied on two milled steel surfaces, one convex with an evident large scale, cylindrical form anisotropy, the other nominally flat with smaller scale anisotropies; a µEDMed surface, an example of an isotropic surface; and an additively manufactured surface with pillar-like features. Curvature tensors contain the two principal curvatures, i.e., maximum and minimum curvatures, which are orthogonal, and their directions, at each location. Principal directions are plotted for each calculated location on each surface, at each scale considered. Histograms in horizontal coordinates show altitude and azimuth angles of principal curvatures, elucidating dominant texture directions at each scale. Str and Std do not show vertical components, i.e., altitudes, of anisotropy. Changes of anisotropy with scale categorically failed to be detected by traditional characterization methods used conventionally. These multiscale methods show clearly in several representations that anisotropy changes with scale on actual surface measurements with markedly different anisotropies.

The objective of this work is to study the geometric properties of surface topographies of hot-work tool steel created by electric discharge machining (EDM) using motif and multiscale analysis. The richness of these analyses is tested through calculating the strengths of the correlations between discharge energies and resulting surface characterization parameters, focusing on the most representative surface features—craters, and how they change with scale. Surfaces were created by EDM using estimated energies from 150 to 9468 µJ and measured by focus variation microscope. The measured topographies consist of overlapping microcraters, of which the geometry was characterized using three different analysis: conventional with ISO parameters, and motif and multiscale curvature tensor analysis. Motif analysis uses watershed segmentation which allows extraction and geometrically characterization of each crater. Curvature tensor analysis focuses on the characterization of principal curvatures and their function and their evolution with scale. Strong correlations (R² > 0.9) were observed between craters height, diameter, area and curvature using linear and logarithmic regressions. Conventional areal parameter related to heights dispersion were found to correlate stronger using logarithmic regression. Geometric characterization of process-specific topographic formations is considered to be a natural and intuitive way of analyzing the complexity of studied surfaces. The presented approach allows extraction of information directly relating to the shape and size of topographic features of interest. In the tested conditions, the surface finish is mostly affected and potentially controlled by discharge energy at larger scales which is associated with sizes of fabricated craters.

The paper presents the results of tests aimed at evaluating the surface textures of samples manufactured from material based on 316L stainless steel. The analysis of the surface topography was conducted based on the classical approach in accordance with the current standard and with the use of multiscale methods; i.e., wavelet transformation and geometric via curvature. Selective laser melting 3D printing technology was used to produce samples for surface testing. Furthermore, additional assessment of surfaces created as result of milling was conducted. Statistical research demonstrated a differentiation in the distribution of particular morphological features in certain ranges of the analyzed scales.

The objectives of this work are to demonstrate the use of multiscale curvature tensor analysis for characterizing surfaces of stainless steel created by micro-electrical discharge machining (μEDM), and to study the strengths of the correlations between discharge energies and resulting surface curvatures (i.e., principal, Gaussian, or mean curvatures) and how they change with scale. Surfaces were created by μEDM techniques using energies from 18 nJ to 16,500 nJ and measured by confocal microscope. The curvature tensor T is calculated using three proximate unit vectors normal to the surface. The multiscale effect is achieved by changing the size of the sampling interval for the estimation of the normals. Normals are estimated from regular meshes by applying a covariance matrix method. Strong correlations (R²> 0.9) are observed between calculated principal maximal and minimal as well as mean and Gaussian curvatures and discharge energies. This method allows detailed analysis of the nature of surface topographies and suggests that different formation processes governed the creation of surfaces created by higher energies.