<![CDATA[Surface roughness is a critical quality indicator in the CNC milling process, directly influencing the functional performance, fatigue life, and aesthetic quality of machined components. The rapid development of advanced materials and high-precision manufacturing has intensified the need to understand and optimize machining parameters to achieve superior surface integrity. This study aims to systematically analyze the effects of cutting parameters on surface roughness in CNC milling by synthesizing and critically discussing findings from recent experimental and analytical studies. A comprehensive literature-based research method was employed, involving peer-reviewed journal articles indexed internationally and nationally, focusing on milling operations across metallic, composite, polymeric, and wood-based materials. The analysis reveals that feed rate consistently emerges as the most influential parameter affecting surface roughness, followed by cutting speed and depth of cut, although their relative significance varies depending on material properties, tool geometry, lubrication conditions, and machining strategies. Advanced approaches such as Taguchi methods, response surface methodology, and machine learning-based models demonstrate substantial potential in predicting and minimizing surface roughness. The findings confirm that optimal selection and control of cutting parameters can significantly enhance surface quality and machining efficiency. This article contributes a consolidated scientific perspective that can serve as a reference for researchers and practitioners in optimizing CNC milling processes.]]>
