A fundamental analytical model for micro topography of skived gear surface

Surface topography is important for gear components, as it exerts influence on noise, wear, lubrication, and life expectancy. Different gear finishing processes result in varying micro tooth topographies, which lead to different driving and lubricating performances. The advanced technology of gear skiving, a recent industry application known for its high efficiency and flexibility in both roughing and finishing of cylindrical gears, has become the focus of extensive research. However, investigations into the micro topography of skived tooth flanks have been limited, primarily due to the absence of a highly efficient algorithm, which hinders the prediction and optimization of driving performance. By demonstrating that the skived surface can be obtained through the collection of micro-sections of the cutter trace in a specific order, this paper proposes a comprehensive analytical model for the micro topography of the skived surface. Both numerical and experimental studies reveal the topology texture, surface roughness, and the effects of the cutter and cutting settings. Results indicate that a higher installation angle, feed rate, and cutter tooth number are more effective in reducing roughness.