Tool Adaptation Strategy for a High-speed Motorized Spindle Based on Bayesian-optimized Random Forest and Orthogonal Factor-effect Analysis

Introduction/Objective: High-speed motorized-spindle vibration depends jointly on rotational speed, number of flutes, toolholder diameter, and measurement location. This study combines orthogonal analysis with a Bayesian-Optimized Random Forest (BO-RF) to develop a tool adaptation strategy across speed zones. Methods: An L16(45) orthogonal-array experiment used analyzer-integrated peak displacement as the response. A rotor–bearing–toolholder model generated 504 samples covering 42 speeds and 12 combinations of flute number and toolholder diameter. Bayesian optimization tuned random forest hyperparameters using four-fold cross-validation grouped by spindle speed. Out-of-fold predictions from the four fold-specific models ranked all candidates at each speed, and a continuity rule formed five adaptation zones. Results: Speed had the largest range of level means (0.01825 mm) and accounted for 55.6% of the fitted main-effect variation. BO-RF achieved a root-mean-square error of 1.246 × 10⁻³ and a coefficient of determination of 0.9625. The recommendations were 8-flute–φ30 mm at 1,000–5,000 r/min; 6-flute–φ30 mm at 6,000–14,000 r/min; 4-flute–φ25 mm at 15,000–20,000 r/min; 6-flute–φ20 mm at 21,000–30,000 r/min; and 4-flute–φ20 mm at 31,000–42,000 r/min. Relative to the fixed 6-flute–φ25 mm baseline, zonal improvements ranged from 14.10% to 24.95%, and the mean predicted index across all speeds decreased by 20.10%. Under representative 6-flute conditions, the relative differences between simulated and experimental displacement responses averaged over the speed range were 2.41%–3.02%. Discussion: Speed dominated the measured main effects, while preferred specifications reflected stiffness, rotating mass, and excitation–modal proximity. Representative experiments supported the numerical sample source but did not validate every candidate or adaptation zone. Conclusion: The workflow supports quantitative selection of toolholder diameter and flute number across speed zones within the investigated spindle and operating range.