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Index
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Authors
1 Introduction to the Beauty of Response Surface Methods
Strategy of Experimentation: Role for RSM
One Map Better than 1000 Statistics (Apologies to Confucius?)
Using Math Models to Draw a Map That’s Wrong (but Useful!)
Finding the Flats to Achieve Six Sigma Objectives for Robust Design
Appendix 1A: Don’t Let R2 Fool You
2 Lessons to Learn from Happenstance Regression
Dangers of Happenstance Regression
The Storks-Bring-Babies Fallacy, in Which Correlation Implies Causation
Diagnosing Input and Output Data for Outlying and/or Influential Points
Extrapolation Can Be Hazardous to Your Health!
Appendix 2A: A Brief Overview of Matrix Terminology
3 Factorials to Set the Stage for More Glamorous RSM Designs
Putting OFAT in the Fire
Factorial Designs as an Option to OFAT
Two-Level Factorial Design with CPs: A Foundation for RSM
A Test for Curvature Tailored to 2k Designs with CPs
Further Discussion on Testing for Lack of Fit (LOF)
The Fork in the Road Has Been Reached!
4 Central Composite Design: Stars Added—RSM Show Begins
Augmenting a Two-Level Factorial with Star Points to Fit Curvature
CCD Example: Part Two of Chemical Reaction Example
How to Select a Good Predictive Model
Inspecting the Selected Model
Model Graphs
Appendix 4A: Details for Sequential Model Sum of Squares Table
Appendix 4B: Details for Lack of Fit Tests
5 Three-Level Designs
The Box-Behnken Design (BBD)
Case Study on Trebuchet
Appendix 5A: Box-Cox Plot for Transformations
6 Finding Your Sweet Spot for Multiple Responses
“Less Filling” versus “Tastes Great!”: Always a Tradeoff
Making Use of the Desirability Function to Evaluate Multiple Responses
Numerical Search for the Optimum
Summary
Case Study with Multiple Responses: Making Microwave Popcorn
Appendix 6A: Simplex Optimization
7 Computer-Generated Optimal Designs
Quantifying Operating Boundaries with Multilinear Constraints
Computer-Generated Design for Constrained Region of Interest
A Real-Life Application for Computer-Generated Optimal Design
Other Applications for Optimal Designs
Appendix 7A: How to Quantify Multilinear Constraints
Appendix 7B: How to Generate a Good Candidate Set
Appendix 7C: An Algorithm for Optimal Point Selection
8 Everything You Should Know about CCDs (but Dare Not Ask!)
Rotatable Central Composite Designs (CCDs)
Going Cuboidal When Your Region of Operability and Interest Coincide
Practical Placement of Stars: Outside the Box but Still in the Galaxy
CPs in Central Composite Designs
Final Comments: How We Recommend That You Construct CCDs
Appendix 8A: Some Details on Blocking CCDs and Issues of Orthogonality
Appendix 8B: Small Composite Designs (SCDs) to Minimize Runs
Good Alternative to SCDs: Minimum-Run Resolution V CCDs
9 RSM for Six Sigma
Developing POE at the Simplest Level of RSM: A One-Factor Experiment
An Application of POE for Three Factors Studied via a BBD
Appendix 9A: Details on How to Calculate POE
POE for Transformed Responses
10 Other Applications for RSM
Adding Categoric Factors to RSM Designs
RSM for Experimenting on Computer Simulations
Appendix 10A: Alternative RSM Designs for Experiments on Simulations
11 Applying RSM to Mixtures
Accounting for Proportional Effects by Creating Ratios of Ingredients
A Different Approach for Optimizing Formulations: Mixture Design
12 Practical Aspects for RSM Success
Split Plots to Handle HTC Factors
Right-Sizing Designs via Fraction of Design Space Plots
How to Confirm Your Models
Glossary
References
Index
About the Software
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