Prediction and Optimization of Freeform Impeller Machining Parameters Using a Hybrid Taguchi-Artificial Neural Network Model with the Levenberg–Marquardt Algorithm
Freeform machining of impellers involves extended cycle times, leading to high energy consumption and costs necessitating efficient process optimization. This study develops a CAD/CAM-integrated hybrid Taguchi-Artificial Neural Network (ANN) model to optimize machining parameters for a freeform impeller. Four controlla...