Enhancing Surface Quality in Micro End-Milling of Ultrafine-Grained Low Carbon Steel Micromolds Through Strategic Toolpath Selection

Abstract Surface quality in micromachining significantly affects the performance and functionality of high-precision components, especially in fields such as aerospace, medical devices, and microelectronics. The selection of toolpath strategy, cutting speed, and feed per tooth determines both surface roughness and texture characteristics, which influence wear resistance, fluid dynamics, and overall part behavior. This study explores the impact of three toolpath strategies—Helical, Offset, and Raster—on the surface quality of micromilled ultrafine-grained low carbon steel micromolds, using cutting speeds of 40 m/min and 100 m/min, and feed per tooths of 2 µm/tooth and 8 µm/tooth. Surface roughness parameters (Sa, Sq, Sz) and texture descriptors (Sal, Str) were examined under these varying cutting conditions. The Helical toolpath consistently produced smoother and more isotropic surfaces at lower feed per tooth, making it suitable for applications requiring high surface uniformity, such as optical components and tribological parts. In contrast, the Raster toolpath generated finer, anisotropic features at higher feed per tooths, beneficial for directional flow applications like microfluidic devices. The Offset toolpath offered a balanced outcome between the two, providing moderate roughness and texture uniformity. Statistical analysis (ANOVA) confirmed the significant influence of feed per tooth and cutting speed on texture. These results highlight the importance of optimizing machining parameters to achieve tailored surface characteristics for advanced engineering applications.