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Demonstrates improved drilling outcomes in bone surgery, highlighting effective parameter optimization techniques.
The drilling force, temperature and surface roughness during bone drilling critically determine bone tissue trauma and surgical performance. To address the difficulty of coordinating multiple conflicting indicators through single-objective optimization, this study conducts multi-objective parameters optimization of low-frequency vibration-assisted bone drilling. Central Composite Design (CCD) is employed to establish quadratic regression models for drilling force, drilling temperature and surface roughness with spindle speed, feed rate, voltage (amplitude), and vibration frequency as input variables. Model validity is confirmed via analysis of variance and residual analysis. Taking the simultaneous minimization of the three machining responses as the objective, the genetic algorithm (NSGA-II) is applied to acquire Pareto optimal solutions. The optimal parameter combination is determined as: spindle speed 2000 rpm, feed rate 0.18 mm/s, voltage 200 V, frequency 170 Hz. Corresponding predicted values are 35 N (drilling force), 61°C (temperature) and 1.05 μm (surface roughness). Validation experiments show that the prediction error of each indicator is within 15%, verifying the reliability of the proposed optimization method. Furthermore, when combined with drill bit pre-cooling, the drilling temperature decreased to 50.3°C, while drilling force and surface roughness remain at low levels. This study provides a low-damage, high-quality process parameter optimization method for bone drilling surgery, offering significant clinical application value.
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Han et al. (2026) studied this question.
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