MODELING MICRO- AND MACRO-GEOMETRIC ERROR FORMATION IN SIDE MILLING AND DEVELOPMENT OF A G-CODE-BASED ADAPTIVE COMPENSATION ALGORITHM

The dimensional and geometric accuracy of side milling operations is directly influenced by the interaction of micro- and macro-geometric error sources occurring throughout the machining process. Micro-geometric errors mainly arise from tool wear, cutting-edge radius variation, spindle runout, tool deflection, vibration, and thermal deformation, whereas macro-geometric errors are associated with machine tool kinematic inaccuracies, positioning deviations, fixture misalignment, and structural deformation. These error mechanisms significantly affect surface integrity, dimensional precision, and process stability, particularly in the manufacturing of high-precision components for aerospace, automotive, mold-making, and medical industries. This study proposes an integrated modeling framework for the simultaneous prediction of micro- and macro-geometric error formation during side milling. The proposed approach combines geometric error modeling, machining dynamics, cutting force analysis, and tool-path deviation assessment to establish a comprehensive error propagation model. Based on the predicted deviations, an adaptive compensation algorithm is developed using G-code modification principles, enabling automatic correction of machining paths before execution. The compensation strategy dynamically adjusts coordinate values according to estimated geometric deviations without requiring additional hardware or machine tool modifications. The research contributes to the advancement of intelligent CNC machining by integrating predictive geometric error modeling with adaptive G-code optimization. The proposed framework provides a practical and scalable solution for enhancing machining precision in modern smart manufacturing environments and supports the implementation of Industry 4.0-based adaptive machining systems.