Dynamic response and geometric modeling of cutting engagement under varying tool inclination in robotic milling of SiCp/Al composites

Robotic milling has emerged as a promising approach for the precision machining of large and complex particle-reinforced metal matrix composites, owing to its superior flexibility and cost-effectiveness. However, the inherently low structural stiffness of robotic systems poses significant challenges to cutting stability and surface quality. In this study, the influence of tool inclination angle on vibration characteristics and machined surface integrity was systematically investigated. Milling experiments were conducted using a six-axis industrial robot across seven inclination angles ranging from −15° to +15°. Vibration signals were acquired and analyzed through empirical mode decomposition (EMD), recurrence plots (RP), frequency-domain analysis, and kernel density estimation (KDE). Additionally, impulse factor (IF) and margin factor (MF) parameters were employed to quantify time-domain vibration stability. Results show that inclination angles of 0° and − 10° lead to the lowest vibration amplitudes and the smoothest surface finish. A geometric model of the tool–workpiece interaction was developed to interpret the formation mechanisms of burrs and surface features. Compared with positive inclinations, negative angles facilitate more symmetric cutting, suppressing force pulsation and enhancing dynamic stability. This study demonstrates that the surface quality in robotic milling is governed not solely by tool geometry but by the coupled effects of tool inclination, cutting-induced vibrations, and robot structural compliance. These findings provide theoretical and practical guidance for tool posture optimization in robotic machining of particle-reinforced composites.