Praise for the Third Edition: “This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.” - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.
This is the first edited volume on response surface methodology (RSM).
Box, G. E. P. and Draper, N. R. (1987) Empirical Model Building and Response Surfaces, New York: John Wiley. 5. ... Peterson, J. J. (1988), "A General Approach to Ridge Analysis with Confidence Intervals", Technical Report S-44, ...
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...
This edition contains chapters on response surface models with block effects and on Taguchi's robust parameter design, additional details on transformation of response variable, more material on modified ridge analysis, and new design ...
This book continues where DOE Simplified leaves off in Chapter 8 with an introduction to "Response Surface Methods [RSM] for Optimization.
This book not only presents a theoretical overview about the different approaches but also contains material that covers the use of the experimental analysis applied to several chemical processes.
How can I deliver tailored Response surface methodology advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk.
George E. P. Box, Norman R. Draper. Ž. Lind, E. E., Goldin, J., and Hickman, J. B. 1960. Fitting yield and cost response surfaces. Chemical Engineering Progress, 56, 62. Ž. Lindsay, B. G. 1989a. On the determinants of moment matrices.
The book is a joy to read. Everyone who practices or teaches DOE should read this book.
The shift to modelling food processes as a way of identifying and understanding the key variables at work is a major outgrowth of this trend.The editors and contributors explore the current trends in modelling, their strengths, and ...