Response Surface Methodology: Process and Product Optimization Using Designed ExperimentsPraise for the Second Edition: "This book [is for] anyone who would like a good, solid understanding of response surface methodology. The book is easy to read, easy to understand, and very applicable. The examples are excellent and facilitate learning of the concepts and methods." Complete with updates that capture the important advances in the field of experimental design, Response Surface Methodology, Third Edition successfully provides a basic foundation for understanding and implementing response surface methodology (RSM) in modern applications. The book continues to outline the essential statistical experimental design fundamentals, regression modeling techniques, and elementary optimization methods that are needed to fit a response surface model from experimental data. With its wealth of new examples and use of the most up-to-date software packages, this book serves as a complete and modern introduction to RSM and its uses across scientific and industrial research. This new edition maintains its accessible approach to RSM, with coverage of classical and modern response surface designs. Numerous new developments in RSM are also treated in full, including optimal designs for RSM, robust design, methods for design evaluation, and experiments with restrictions on randomization as well as the expanded integration of these concepts into computer software. Additional features of the Third Edition include:
Assuming only a fundamental background in statistical models and matrix algebra, Response Surface Methodology, Third Edition is an ideal book for statistics, engineering, and physical sciences courses at the upper-undergraduate and graduate levels. It is also a valuable reference for applied statisticians and practicing engineers. |
Contents
Building Empirical Models | 13 |
of Coefficients | 27 |
TwoLevel Factorial Designs | 73 |
TwoLevel Fractional Factorial Designs | 135 |
Process Improvement with Steepest Ascent | 181 |
The Analysis of SecondOrder Response Surfaces | 219 |
Standard Error of Predicted Response | 243 |
Experimental Designs for Fitting Response SurfacesI | 281 |
Examples of Noise Variables | 484 |
Response Surfaces | 506 |
Use of Generalized Linear Models | 521 |
Exercises | 548 |
Experiments with Mixtures | 557 |
a Constant Term b0 | 577 |
Other Mixture Design and Analysis Techniques | 589 |
281 | 594 |
Experimental Designs for Fitting Response SurfacesII 8 1 Designs that Require a Relatively Small Run Size | 350 |
Practical Design Optimality | 365 |
Advanced Topics in Response Surface Methodology | 417 |
3 | 423 |
135 | 431 |
7 | 449 |
Exercises | 476 |