DOE Simplified: Practical Tools for Effective Experimentation

Abstract

Basic Statistics for DOE The X Factors Does Normal Distribution Ring Your Bell? Descriptive Statistics: Mean and Lean Confidence Intervals Help You Manage Expectations Graphical Tests Provide Quick Check for Normality Practice Problems Simple Comparative Experiments The F-Test Simplified A Dicey Situation: Making Sure They Are Fair Catching Cheaters with a Simple Comparative Experiment Blocking Out Known Sources of Variation Practice Problems Two-Level Factorial Design Two-Level Factorial Design: As Simple as Making Microwave Popcorn How to Plot and Interpret Interactions Protect Yourself with Analysis of Variance (ANOVA) Modeling Your Responses with Predictive Equations Diagnosing Residuals to Validate Statistical Assumptions Practice Problems Appendix: How to Make a More Useful Pareto Chart Dealing with Nonnormality via Response Transformations Skating on Thin Ice Log Transformation Saves the Data Choosing the Right Transformation Practice Problem Fractional Factorials Example of Fractional Factorial at Its Finest Potential Confusion Caused by Aliasing in Lower Resolution Factorials Plackett-Burman Designs Irregular Fractions Provide a Clearer View Practice Problem Getting the Most from Minimal-Run Designs Minimal-Resolution Design: The Dancing Raisin Experiment Complete Foldover of Resolution III Design Single-Factor Foldover Choose a High-Resolution Design to Reduce Aliasing Problems Practice Problems Appendix: Minimum-Run Designs for Screening General Multilevel Categoric Factorials Putting a Spring in Your Step: A General Factorial Design on Spring Toys How to Analyze Unreplicated General Factorials Practice Problems Appendix: Half-Normal Plot for General Factorial Designs Response Surface Methods for Optimization Center Points Detect Curvature in Confetti Augmenting to a Central Composite Design (CCD) Finding Your Sweet Spot for Multiple Responses Mixture Design Two-Component Mixture Design: Good as Gold Three-Component Design: Teeny Beany Experiment Back to the Basics: The Keys to Good DOE A Four-Step Process for Designing a Good Experiment A Case Study Showing Application of the Four-Step Design Process Appendix: Details on Power Managing Expectations for What the Experiment Might Reveal Increase the Range of Your Factors Decrease the Noise (sigma) in Your System Accept Greater Risk of Type I Error (alpha) Select a Better and/or Bigger Design Split-Plot Designs to Accommodate Hard-to-Change Factors How Split Plots Naturally Emerged for Agricultural Field Tests Applying a Split Plot to Save Time Making Paper Helicopters Trade-Off of Power for Convenience When Restricting Randomization One More Split Plot Example: A Heavy-Duty Industrial One Practice Experiments Practice Experiment #1: Breaking Paper Clips Practice Experiment #2: Hand-Eye Coordination Other Fun Ideas for Practice Experiments Ball in Funnel Flight of the Balsa Buzzard Paper Airplanes Impact Craters Appendix 1 Two-Tailed t-Table F-Table for 10% F-Table for 5% F-Table for 1% F-Table for 0.1% Appendix 2 Four-Factor Screening and Characterization Designs Screening Main Effects in 8 Runs Screening Design Layout Alias Structure Characterizing Interactions with 12 Runs Characterization Design Layout Alias Structure for Factorial Two-Factor Interaction Model Alias Structure for Factorial Main Effect Model Five-Factor Screening and Characterization Designs Screening Main Effects in 12 Runs Screening Design Layout Alias Structure Characterizing Interactions with 16 Runs Design Layout Alias Structure for Factorial Two-Factor Interaction (2FI) Model Six-Factor Screening and Characterization Designs Screening Main Effects in 14 Runs Screening Design Layout Alias Structure Characterizing Interactions with 22 Runs Design Layout Alias Structure for Factorial Two-Factor Interaction (2FI) Model Seven-Factor Screening and Characterization Designs Screening Design Layout Alias Structure Characterizing Interactions with 30 Runs Design Layout Alias Structure for Factorial Two-Factor Interaction (2FI) Model Glossary Statistical Symbols Terms Recommended Readings Textbooks Case Study Articles Index

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