Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Enhancing interfacial contact bearing performance typically involves minimizing the roughness parameter Sa (arithmetic mean height). Yet, exceedingly low Sa incur steep increases in processing costs, indicating that Sa - centric optimization strategies may not be universally suitable for interface performance control. Roughness parameters skewness ( Ssk ) and kurtosis ( Sku ) exert a pronounced influence on component contact wear performance. Accordingly, investigating the correlation between Ssk , Sku , and wear performance holds significant promise for enhancing wear resistance. A finite element wear calculation model for rough-surface abrasive wear employing elastic-plastic contact mechanics and the Jump-in-Cycle method. Cylindrical roller dry sliding experiments validate the model ' s reliability. Integrating this model, a method is proposed for wear performance discrimination based on Sa and Ssk at different loads. It enables the identification of critical roughness parameter values for improved surface wear resistance. The calculated wear model aligns with experiment trends, with predicted surface textures mirroring observed wear surface characteristics. Critical Sa and Ssk diverge under distinct loads. The study underscores the importance of moving beyond the exclusive pursuit of exceptionally low Sa and Ssk . It provides a foundation for reducing workpiece processing costs while optimizing wear performance.