EE731:DESIGN OF EXPERIMENT /TAGUCHI METHOD FOR EXPERIMENTAL RESEARCH
Fundamentals of classical statistical methods: Normal Probability distribution, Statistical analysis of Means and Variance, Evolution of Taguchi Methods.;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.;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.;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.
M.S. Phadke, "Quality Engineering using Robust Design" Prentice Hall (1989).