Efficient Surface Topography Prediction Using Enhanced Z-MAP Algorithms for Ball End Milling Process

Surface topography is a critical factor influencing the precision, performance, and longevity of machined parts. Modeling and simulating surface topography for various milling processes, particularly 5-axis high-speed milling, remains an essential area of study to enhance manufacturing accuracy and efficiency. This work explores advancements in Z-MAP algorithms, widely used to model the topography of surfaces for ball end milling process (BEMP), and evaluates recent techniques to improve computational efficiency while maintaining accuracy. A Z-MAP algorithm is proposed that uses the Cutter Workpiece Engagement Region (CWER) calculation to minimize computation time. This method provides a robust solution to the conventional approach's limitations, enabling accurate surface topography simulation under diverse milling parameters with optimized efficiency. This paper presents the validation of a Z-MAP algorithm integrating CWER, using experimental data from 3-axis and tilt orientation of the tool.