Page d'explications sur les plans d'expériences 

Design of Experiments: Science, Industrial DOE

• DOE Overview
  • Experiments in Science and Industry
  • Differences in techniques
  • Overview
  • General Ideas
  • Computational Problems
  • Components of Variance, Denominator Synthesis
  • Summary
• 2**(k-p) Fractional Factorial Designs
  • Basic Idea
  • Generating the Design
  • The Concept of Design Resolution
  • Plackett-Burman (Hadamard Matrix) Designs for Screening
  • Enhancing Design Resolution via Foldover
  • Aliases of Interactions: Design Generators
  • Blocking
  • Replicating the Design
  • Adding Center Points
  • Analyzing the Results of a 2**(k-p) Experiment
  • Graph Options
  • Summary
• 2**(k-p) Maximally Unconfounded and Minimum Aberration Designs
  • Basic Idea
  • Design Criteria
  • Summary
• 3**(k-p) , Box-Behnken, and Mixed 2 and 3 Level Factorial Designs
  • Overview
  • Designing 3**(k-p) Experiments
  • An Example 3**(4-1) Design in 9 Blocks
  • Box-Behnken Designs
  • Analyzing the 3**(k-p) Design
  • ANOVA Parameter Estimates
  • Graphical Presentation of Results
  • Designs for Factors at 2 and 3 Levels
• Central Composite and Non-Factorial Response Surface Designs
  • Overview
  • Design Considerations
  • Alpha for Rotatability and Orthogonality
  • Available Standard Designs
  • Analyzing Central Composite Designs
  • The Fitted Response Surface
  • Categorized Response Surfaces
• Latin Square Designs
  • Overview
  • Latin Square Designs
  • Analyzing the Design
  • Very Large Designs, Random Effects, Unbalanced Nesting
• Taguchi Methods: Robust Design Experiments
  • Overview
  • Quality and Loss Functions
  • Signal-to-Noise (S/N) Ratios
  • Orthogonal Arrays
  • Analyzing Designs
  • Accumulation Analysis
  • Summary
• Mixture designs and triangular surfaces
  • Overview
  • Triangular Coordinates
  • Triangular Surfaces and Contours
  • The Canonical Form of Mixture Polynomials
  • Common Models for Mixture Data
  • Standard Designs for Mixture Experiments
  • Lower Constraints
  • Upper and Lower Constraints
  • Analyzing Mixture Experiments
  • Analysis of Variance
  • Parameter Estimates
  • Pseudo-Components
  • Graph Options
• Designs for constrained surfaces and mixtures
  • Overview
  • Designs for Constrained Experimental Regions
  • Linear Constraints
  • The Piepel & Snee Algorithm
  • Choosing Points for the Experiment
  • Analyzing Designs for Constrained Surfaces and Mixtures
• Constructing D- and A-optimal designs
  • Overview
  • Basic Ideas
  • Measuring Design Efficiency
  • Constructing Optimal Designs
  • General Recommendations
  • Avoiding Matrix Singularity
  • "Repairing" Designs
  • Constrained Experimental Regions and Optimal Design
• Special Topics
  • Profiling Predicted Responses and Response Desirability
  • Residuals Analysis
  • Box-Cox Transformations of Dependent Variables