Determined how cutting speed, feed rate, and depth of cut parameters affect the ability to forecast tool life in milling operations using Xgboost Regressor.In this experiment Taguchi DOE was used for performing machining operations.The Xgboost Regressor model predicts excellent tool life with train accuracy of 99.9% and test accuracy of 98.0%
Shows the 3D visualization of dataset and redirects the efficient zone shown by dark red
scatter points for which the range is 360-740 rpm for spindle speed,50-200 mm/min for feed rate
and 0.2-0.7 mm for depth of cut
Dataset- Preprocessing
Actual vs Predicted
