This study focuses on analyzing how various input parameters affect the output parameters of cutting time and cutting site temperature when cutting through chicken and rat femur bones and also aims to provide insights into optimizing cutting processes in these contexts. In this research, two ultrasonic surgical knives were designed and simulated using Abaqus software. The system design was then optimized and the knife parts were assembled after machining. The bone cutting process was performed on chicken femur and rat femur bones using both wet and dry cutting modes with an ultrasonic bone scalpel circuit resonance and saw and sharp-edge blades with vibration amplitudes of 18, 22.5, and 27 µm. The experiments were designed as a full factorial, and an ANN model was used to interpret and predict the cutting responses. Increasing the vibration amplitude from 18 to 27 µm reduced the cutting time by 30% for the sharp-edge blade and 33% for the saw-edge blade in dry cutting and by approximately 30%–40% in wet cutting. The cutting temperature also decreased significantly with increasing amplitude, by approximately 27% (sharp edge) and 30% (saw edge) in dry conditions and by approximately 19% in wet conditions (with two blades). Overall, the saw-edge blade showed a 52%–72% shorter cutting time and 50%–70% lower temperature compared to the sharp-edge blade in both cutting conditions. Finally, the ANN model data results showed a good agreement with the actual data for cutting temperature and time.
Aghdasta et al. (2026) studied this question.