UsefulLinks
Statistics
Design of Experiments
1. Introduction to Design of Experiments
2. Fundamental Principles of Experimental Design
3. Planning and Conducting Experiments
4. Simple Comparative Experiments
5. Analysis of Variance (ANOVA)
6. Factorial Designs
7. Fractional Factorial Designs
8. Response Surface Methodology
9. Robust Design and Taguchi Methods
10. Advanced and Specialized Designs
11. Statistical Analysis and Model Building
12. Software Tools and Implementation
13. Quality Control and Best Practices
14. Applications and Case Studies
8.
Response Surface Methodology
8.1.
RSM Concepts and Objectives
8.1.1.
Response Surface Visualization
8.1.2.
Optimization Goals
8.1.3.
Sequential Nature of RSM
8.1.4.
Design Regions
8.2.
First-Order Response Surface Designs
8.2.1.
Linear Models
8.2.2.
First-Order Designs
8.2.2.1.
2^k Designs
8.2.2.2.
Simplex Designs
8.2.3.
Method of Steepest Ascent
8.2.3.1.
Path Determination
8.2.3.2.
Step Size Selection
8.2.3.3.
Stopping Criteria
8.2.4.
Analysis of First-Order Models
8.3.
Second-Order Response Surface Designs
8.3.1.
Quadratic Models
8.3.2.
Central Composite Designs
8.3.2.1.
Circumscribed CCD
8.3.2.2.
Inscribed CCD
8.3.2.3.
Face-Centered CCD
8.3.2.4.
Alpha Values
8.3.3.
Box-Behnken Designs
8.3.4.
Uniform Shell Designs
8.3.5.
Design Properties
8.3.5.1.
Rotatability
8.3.5.2.
Orthogonality
8.3.5.3.
Efficiency Measures
8.4.
Analysis of Second-Order Models
8.4.1.
Model Fitting
8.4.2.
Lack-of-Fit Testing
8.4.3.
Model Adequacy Assessment
8.4.4.
Canonical Analysis
8.4.4.1.
Stationary Point Location
8.4.4.2.
Nature of Stationary Point
8.4.4.3.
Principal Component Analysis
8.4.5.
Ridge Analysis
8.4.6.
Contour Plot Interpretation
8.4.7.
Optimization Strategies
8.5.
Multiple Response Optimization
8.5.1.
Desirability Functions
8.5.2.
Pareto Optimal Solutions
8.5.3.
Compromise Solutions
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7. Fractional Factorial Designs
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9. Robust Design and Taguchi Methods