Gets you quickly up and running with the full range of powerful statistical experimental design, modeling, and optimization techniques
Coauthored by widely recognized experts in the fields of quality control and the design of experiments, this book is a practical guide to Response Surface Methodology (RSM)—the process of identifying and fitting an appropriate response surface model from experimental data. While in the opening chapters the authors lay down the basic conceptual groundwork preliminary to a working understanding of the methods described, the bulk of the book is devoted to providing students and professionals with clear, step-by-step guidance on the use of powerful statistical and empirical modeling techniques that have proven their efficacy in industry. Throughout, numerous real-world examples help illuminate critical points covered, and chapter-end problems help you to gauge your command of the concepts and procedures described. Important topics covered include:
Providing clear, hands-on guidance to the application of some of today's most useful techniques, Response Surface Methodology is an essential working resource for process development and quality engineering professionals, engineering designers, product formulators, engineers, chemists, and all those whose professional activities involve the design of experiments.
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Using a practical approach, it discusses two-level factorial and fractional factorial designs, several aspects of empirical modeling with regression techniques, focusing on response surface methodology, mixture experiments and robust design techniques. Features numerous authentic application examples and problems. Illustrates how computers can be a useful aid in problem solving. Includes a disk containing computer programs for a response surface methodology simulation exercise and concerning mixtures.
RAYMOND H. MYERS, PhD, is Professor Emeritus in the Department of Statistics at Virginia Polytechnic Institute and State University.
DOUGLAS C. MONTGOMERY, PhD, is Professor in the Department of Industrial Engineering at Arizona State University.
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