INFLUENCE OF INDUCTION HEATING-ASSISTED MILLING ON VIBRATION AMPLITUDE AND SURFACE ROUGHNESS OF SKD61 STEEL: STATISTICAL MODELING, ANOVA, AND PREDICTIVE ANALYSIS

This study presents a comprehensive investigation into the effects of key machining parameters on vibration amplitude ([Formula: see text] and surface roughness (Ra) during high-speed milling of SKD61 steel with induction heating assistance. By using a Taguchi L9 orthogonal array design, the effects of cutting speed ([Formula: see text]–600[Formula: see text]m/min), feed per tooth ([Formula: see text]–0.15 mm/tooth), depth of cut ([Formula: see text]–0.5[Formula: see text]mm), and induction heating temperature ([Formula: see text]–[Formula: see text]C) were systematically analyzed. The results demonstrate that induction heating significantly improves machining stability and surface quality: average surface roughness decreased by up to 50%, while vibration amplitude was reduced by 20–50% compared to room-temperature milling. Analysis of variance (ANOVA) revealed that depth of cut ([Formula: see text] was the most influential factor, contributing 61.27% and 69.45% to vibration amplitude and surface roughness, respectively, followed by induction heating temperature ([Formula: see text] and cutting speed (V). Feed per tooth (f) exhibited minimal influence (≤3%). Nonlinear regression models established via the Gauss–Newton method accurately predicted [Formula: see text]- and Ra, with maximum deviations of 7.69% and 9.88%, respectively. Furthermore, a power-law relationship between vibration amplitude and surface roughness ([Formula: see text], [Formula: see text]) was identified, providing a quantitative basis for process optimization. This work demonstrates the novelty of combining induction heating-assisted milling with statistical modeling and predictive analysis to enhance surface integrity and reduce machining vibrations for hard-to-cut steels. The findings provide actionable guidance for industrial applications, offering an effective approach to improving both surface quality and machining stability in high-precision manufacturing.