Taguchi DOE Orthogonal Array Matrix Generator

This code has 2 objectives - fisrtly to optimise process parameters of MIG Welding of Mild Steel and secondly, predict tensile strength, hardness, operator fatigue, power consumption and time to weld for input of voltage, gas flow rate and distance of weld from user

Here 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%

MATLAB functions for Taguchi Signal-to-Noise Ratio Statistics

Semiconductor Process Control (ECE6455-A) @ Georgia Institute of Technology, Atlanta, GA, USA