Design and Analysis of Experiments Using Taguchi Method

1. Fundamentals of classical statistical methods: Normal Probability distribution; Statistical analysis of Means and Variance; Evolution of Taguchi Methods. 2. Fundamentals of Taguchi Methods: Basic philosophy of Taguchi loss function and robust design; 8-steps in Taguchi Method; P-diagrams of Static and Dynamic problems; Definitions of signal, noise and control factors; Degrees of freedom; Linear graphs and orthogonal arrays and their designs; Definitions of Signal to Noise ratio; Evaluation of sensitivity to noise; Resolution of design; Analysis of Means, Means Plots and Analysis of Variance; Prediction of optimum conditions; Prediction of error variance. 3. Design of Experiments for Robust Design: Identification of signal, noise and control variables; Identification and selection interactions; Control factors and their levels; Strategies for experimentation using Taguchi methods, beginner, intermediate and advanced strategies; Selection of design of orthogonal array, Modification of orthogonal arrays and linear graphs; Performing matrix experiments; Methods of analyzing experimental data; Interpretation of results. 4. Application Examples: Application of design of experiments for circuit design for temperature insensitivity, robust design of sensors with reduced cross-sensitivities, designing robust processes: machining and cutting tool wear analysis, surface quality optimization, metallurgical structure optimization; packaging related wire and die bonding optimization; Application of design of experiments for optimizing product performance and process yield.