arXiv subjects

Matthias Eifler

Publications and source records attributed to Matthias Eifler.

3 recordsLinked to original sources

arXiv2026

Effects of Tool Wear on the Surface Texture in Turning: A Feature Characterization Approach Based on ISO 21920-2

The surface texture of a turned component acts as a fingerprint of both the process parameters and the tool wear condition, imaging the cutting edge. Classical surface parameters such as $R_\mathrm{a}$ or $R_\mathrm{q}$ describe the topography only globally and allow no spatially resolved evaluation of the process-induced deterministic structures. This work investigates how far the feature characterization standardized in ISO 21920-2 makes this wear information accessible and physically interpretable. The database comprises roughness profiles of twelve AlTiN-coated carbide inserts (CNMG120408) machining normalized AISI 1045 steel, measured at nine wear states over the entire tool life, with three replicate profiles per state. The correlation of standardized field and feature parameters with crater wear, flank wear, and cutting time is first examined. Watershed segmentation is then adapted to extract the rotational tool grooves and evaluate their geometry statistically. A newly developed mean-feature approach decomposes the profile into a deterministic and a stochastic component. Wear-induced changes are almost entirely carried by the deterministic component, and within it by the trailing flank of the cutting groove. A comparison with confocal measurements confirms that the mean feature reconstructs the engaged cutting edge geometry, with the trailing-flank steepening attributable to notch wear on the secondary cutting edge. An exhaustive evaluation of more than 920,000 feature characterization combinations and multivariate models reveals that the groove-level mean maximum absolute gradient $\overline{R_\mathrm{dt}}_\mathrm{groove}$ alone explains 83-90% of the variance of the wear indicators, so that a single, physically motivated parameter suffices for robust wear estimation. A follow-up study will investigate inline monitoring using scattered light sensors.

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arXiv2026

Topographic Temperature: A Maximum-Entropy State Description of Running-In Surfaces

Surface topography governs tribological performance, yet conventional parameters describe either amplitude statistics or spectral content in isolation. We introduce a scale-dependent framework that represents surface height and directional gradient as conjugate coordinates of a structural phase space. The elastic reference energy derived from Persson's contact mechanics theory defines a metric that couples surface geometry to the elastic half-space response. A maximum-entropy formulation yields a canonical state density. In the Gaussian limit this formulation recovers Persson's spectral description exactly, showing that the power spectral density is a complete contact mechanical descriptor only under Gaussian statistics. The associated Lagrange multiplier defines a topographic temperature in the sense of Grmela's multiscale thermodynamics and embeds the areal subsystem within a scale-dependent boundary potential. The framework is validated experimentally using ground and honed AISI 52100 steel discs before and after running in. The ground surface contracts toward lower entropy and elastic energy, whereas the honed surface expands into previously unoccupied states. These opposite trajectories become transparent only in the coupled height-gradient representation and highlight the role of the principal directional gradient for scale-aware surface metrology.

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arXiv2024

Feature Characterization for Profile Surface Texture

Conventional field parameters for surface measurement use all data points, while feature characterization focuses on subsets extracted by watershed segmentation. This approach enables the extraction of specific features that are potentially responsible for the function of the surface or are a direct reflection of the manufacturing process, allowing for a more accurate assessment of both aspects. Feature characterization with the underlying watershed segmentation for areal surface topographies has been standardized for over a decade and is well established in industry and research. In contrast, feature characterization for surface profiles has been standardized recently, and the corresponding standard for watershed segmentation is planned to be published in the near future. Since the standards do not provide guidelines for implementation, this paper presents an unambiguous algorithm of the watershed segmentation and the feature characterization for surface profiles. This framework provides the basis for future work, mainly investigating the relationship between feature parameters based on feature characterization and the function of the surface or manufacturing process. For this purpose, recommendations for the configuration and extensions of the toolbox can also be developed, which could find their way into the ISO standards.

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