In today's high-technology world, with flourishing e-business and intense competition at a global level, the search for the competitive advantage has become a crucial task of corporate executives. Quality, formerly considered a secondary expense, is now universally recognized as a necessary tool. Although many statistical methods are available for determining quality, there has been no guide to easy learning and implementation until now. Filling that gap, Statistical Design of Experiments with Engineering Applications, provides a ready made, quick and easy-to-learn approach for applying design of experiments techniques to problems. The book uses quality as the main theme to explain various design of experiments concepts.
The authors examine the entire product lifecycle and the tools and techniques necessary to measure quality at each stage. They explain topics such as optimization, Taguchi's method, variance reduction, and graphical applications based on statistical techniques. Wherever applicable the book supplies practical rules of thumb, step-wise procedures that allow you to grasp concepts quickly and apply them appropriately, and examples that demonstrate how to apply techniques. Emphasizing the importance of quality to products and services, the authors include concepts from the field of Quality Engineering. Written with an emphasis on application and not on bogging you down with the theoretical underpinnings, the book enables you to solve 80% of design problems without worrying about the derivation of mathematical formulas.
Table of Contents
What Is Experimental Design?
Applications of Experimental Design
Old Philosophy of Quality
New Philosophy of Quality
Goals and Outline of Design of Experiments
DESIGNING AND CONDUCTING EXPERIMENTS
Two-Level Factorial Designs
OPTIMIZATION OF THE LOCATION PARAMETER
Guidelines for Location Optimization
Replicated Experimental Runs
An Alternative Approach to the Pareto Chart
MINIMIZATION OF THE DISPERSION
Dispersion Minimization for Replicated Study
Dispersion Minimization for Unreplicated Study
TAGUCHI'S APPROACH TO THE DESIGN OF EXPERIMENTS
Applications of Taguchi's Approach to Robust Designs
Comments on the Taguchi Method
STATISTICAL OPTIMIZATION OF THE LOCATION PARAMETER
Replicated Two-Level Full Factorial Design
Unreplicated Two-Level Full Factorial Design
Two-Level Fractional Factorial Design
STATISTICAL MINIMIZATION OF THE DISPERSION PARAMETER
VALIDITY OF THE PREDICTION EQUATION
Adjusted Coefficient of Determination
F Test for Lack of Fit
THREE-LEVEL FACTORIAL DESIGNS
Three-Level Full Factorial Design
Central Composite Designs
Three-Level Taguchi Designs
Second Order Model in Matrix Terms
Estimation of the Second-Order Model Parameters
Estimation of the First-Order Model Parameters
Fitting a Second-Order Model
Inferences About Regression Parameters
Confidence Limits for Predicted Values
Validity of the Prediction Equation
Appendix 1: Two-Level Fractional Factorial Designs
Appendix 2: Plackett-Burman Designs
Appendix 3: Taguchi Designs
Appendix 4: Standardized Normal Distribution
Appendix 5: Percentiles of t Distribution
Appendix 6: Percentiles of the F Distribution
Appendix 7: Some Useful Box-Behken Designs
Appendix 8: Matrix Algebra
"…provides easy to understand and fast-learning approaches to applying experimental design methods to solving variety of problems that occur in practice. Statistical design principles and complicated concepts are explained very nicely (with minimal mathematical details) using simple examples drawn from engineering and related fields. Inclusion of several chapters on location and dispersion optimization techniques makes this book more useful than other traditional textbooks on experimental design. The authors emphasize more on design techniques than on estimation and analyses which is what gives new dimension. In all, this book is a welcome addition and one that will prove highly successful."
-Prof. Ibrahim A. Ahmad, Dept. of Statistics & Actuarial Science, University of Central Florida, Orlando, USA
"This volume offers a pared-down tour of response surfaces that 'avoids frustrating and unnecessary time spent on theory'. Although it has the feel of a series of lists, it provides a useful introduction to readers who are happy with such an approach."
-N.R. Draper, Short Book Reviews of the ISI
"This book is more suitable (for an engineering audience) than some others that include detailed mathematical derivations and proofs. …Its style is intuitive and prescriptive, and quite readable."
-Journal of the Royal Statistical Society, Series A
"…the structure adopted by the authors is really nice for people who like learning using a recipe-type approach....Another good point for academics is the number of examples that can be reused; for instance, for classroom exams."
structure adopted by the authors is really nice for people who like learning using a recipe-type approach....Another good point for academics is the number of examples that can be reused; for instance, for classroom exams."
||September 27, 2016
To gain access to the instructor resources for this title, please visit the Instructor Resources Download Hub.
You will be prompted to fill out a registration form which will be verified by one of our sales reps.