JMP 10 Design of Experiments Guide

JMP 10 Design of Experiments Guide

Released March 2012
Publisher(s): SAS Institute
ISBN: 9781612902180

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Book description

The JMP 10 Design of Experiments Guide contains information about the JMP Design of Experiments (DOE) platform, including the JMP Custom Designer. This book covers a wide variety of designs including design evaluation, screening, response surface, full factorial, discrete choice, space-filling, non-linear, Taguchi, augmented, mixture designs, and more.

Table of contents

  1. Cover Page
  2. Title Page
  3. Copyright Page
  4. Contents
  5. Learn About JMP
    1. Book Conventions
    2. JMP Documentation
      1. JMP Documentation Suite
      2. JMP Help
      3. JMP Books by Users
      4. JMPer Cable
    3. Additional Resources for Learning JMP
      1. Tutorials
      2. The JMP Starter Window
      3. Sample Data Tables
      4. Learn about Statistical and JSL Terms
      5. Learn JMP Tips and Tricks
      6. Tooltips
      7. Access Resources on the Web
  6. Introduction to Designing Experiments
    1. About Designing Experiments
    2. My First Experiment
      1. The Situation
      2. Step 1: Design the Experiment
      3. Step 2: Define Factor Constraints
      4. Step 3: Add Interaction Terms
      5. Step 4: Determine the Number of Runs
      6. Step 5: Check the Design
      7. Step 6: Gather and Enter the Data
      8. Step 7: Analyze the Results
  7. Examples Using the Custom Designer
    1. Creating Screening Experiments
      1. Creating a Main-Effects-Only Screening Design
      2. Creating a Screening Design to Fit All Two-Factor Interactions
      3. A Compromise Design Between Main Effects Only and All Interactions
      4. Creating ‘Super’ Screening Designs
      5. Screening Designs with Flexible Block Sizes
      6. Checking for Curvature Using One Extra Run
    2. Creating Response Surface Experiments
      1. Exploring the Prediction Variance Surface
      2. Introducing I-Optimal Designs for Response Surface Modeling
      3. A Three-Factor Response Surface Design
      4. Response Surface with a Blocking Factor
    3. Creating Mixture Experiments
      1. Mixtures Having Nonmixture Factors
      2. Experiments that are Mixtures of Mixtures
    4. Special Purpose Uses of the Custom Designer
      1. Designing Experiments with Fixed Covariate Factors
      2. Creating a Design with Two Hard-to-Change Factors: Split Plot
    5. Technical Discussion
  8. Building Custom Designs
    1. Creating a Custom Design
      1. Enter Responses and Factors into the Custom Designer
      2. Describe the Model
      3. Specifying Alias Terms
      4. Select the Number of Runs
      5. Understanding Design Evaluation
      6. Specify Output Options
      7. Make the JMP Design Table
    2. Creating Random Block Designs
    3. Creating Split Plot Designs
    4. Creating Split-Split Plot Designs
    5. Creating Strip Plot Designs
    6. Special Custom Design Commands
      1. Save Responses and Save Factors
      2. Load Responses and Load Factors
      3. Save Constraints and Load Constraints
      4. Set Random Seed: Setting the Number Generator
      5. Simulate Responses
      6. Save X Matrix: Viewing the Number of Rows in the Moments Matrix and the Design Matrix (X) in the Log
      7. Optimality Criterion
      8. Number of Starts: Changing the Number of Random Starts
      9. Sphere Radius: Constraining a Design to a Hypersphere
      10. Disallowed Combinations: Accounting for Factor Level Restrictions
      11. Advanced Options for the Custom Designer
    7. Assigning Column Properties
      1. Define Low and High Values (DOE Coding) for Columns
      2. Set Columns as Factors for Mixture Experiments
      3. Define Response Column Values
      4. Assign Columns a Design Role
      5. Identify Factor Changes Column Property
    8. How Custom Designs Work: Behind the Scenes
  9. Screening Designs
    1. Screening Design Examples
      1. Using Two Continuous Factors and One Categorical Factor
      2. Using Five Continuous Factors
    2. Creating a Screening Design
      1. Enter Responses
      2. Enter Factors
      3. Choose a Design
      4. Display and Modify a Design
      5. Specify Output Options
      6. View the Design Table
    3. Create a Plackett-Burman design
    4. Analysis of Screening Data
      1. Using the Screening Analysis Platform
      2. Using the Fit Model Platform
  10. Response Surface Designs
    1. A Box-Behnken Design: The Tennis Ball Example
      1. The Prediction Profiler
      2. A Response Surface Plot (Contour Profiler)
      3. Geometry of a Box-Behnken Design
    2. Creating a Response Surface Design
      1. Enter Responses and Factors
      2. Choose a Design
      3. Specify Output Options
      4. View the Design Table
  11. Full Factorial Designs
    1. The Five-Factor Reactor Example
      1. Analyze the Reactor Data
    2. Creating a Factorial Design
      1. Enter Responses and Factors
      2. Select Output Options
      3. Make the Table
  12. Mixture Designs
    1. Mixture Design Types
    2. The Optimal Mixture Design
    3. The Simplex Centroid Design
      1. Creating the Design
      2. Simplex Centroid Design Examples
    4. The Simplex Lattice Design
    5. The Extreme Vertices Design
      1. Creating the Design
      2. An Extreme Vertices Example with Range Constraints
      3. An Extreme Vertices Example with Linear Constraints
      4. Extreme Vertices Method: How It Works
    6. The ABCD Design
    7. Creating Ternary Plots
    8. Fitting Mixture Designs
      1. Whole Model Tests and Analysis of Variance Reports
      2. Understanding Response Surface Reports
    9. A Chemical Mixture Example
      1. Create the Design
      2. Analyze the Mixture Model
      3. The Prediction Profiler
      4. The Mixture Profiler
      5. A Ternary Plot of the Mixture Response Surface
  13. Discrete Choice Designs
    1. Introduction
    2. Create an Example Choice Experiment
    3. Analyze the Example Choice Experiment
    4. Design a Choice Experiment Using Prior Information
    5. Administer the Survey and Analyze Results
      1. Initial Choice Platform Analysis
      2. Find Unit Cost and Trade Off Costs with the Profiler
  14. Space-Filling Designs
    1. Introduction to Space-Filling Designs
    2. Sphere-Packing Designs
      1. Creating a Sphere-Packing Design
      2. Visualizing the Sphere-Packing Design
    3. Latin Hypercube Designs
      1. Creating a Latin Hypercube Design
      2. Visualizing the Latin Hypercube Design
    4. Uniform Designs
    5. Comparing Sphere-Packing, Latin Hypercube, and Uniform Methods
    6. Minimum Potential Designs
    7. Maximum Entropy Designs
    8. Gaussian Process IMSE Optimal Designs
    9. Borehole Model: A Sphere-Packing Example
      1. Create the Sphere-Packing Design for the Borehole Data
      2. Guidelines for the Analysis of Deterministic Data
      3. Results of the Borehole Experiment
  15. Accelerated Life Test Designs
    1. Overview of Accelerated Life Test Designs
    2. Using the ALT Design Platform
    3. Platform Options
    4. Example
  16. Nonlinear Designs
    1. Examples of Nonlinear Designs
      1. Using Nonlinear Fit to Find Prior Parameter Estimates
      2. Creating a Nonlinear Design with No Prior Data
    2. Creating a Nonlinear Design
      1. Identify the Response and Factor Column with Formula
      2. Set Up Factors and Parameters in the Nonlinear Design Dialog
      3. Enter the Number of Runs and Preview the Design
      4. Make Table or Augment the Table
    3. Advanced Options for the Nonlinear Designer
  17. Taguchi Designs
    1. The Taguchi Design Approach
    2. Taguchi Design Example
      1. Analyze the Data
    3. Creating a Taguchi Design
      1. Detail the Response and Add Factors
      2. Choose Inner and Outer Array Designs
      3. Display Coded Design
      4. Make the Design Table
  18. Evaluating Experimental Designs
    1. Launching the Evaluate Design Platform
    2. The Evaluate Design Report
    3. Examples
      1. Assessing the Impact of Lost Runs
      2. Assessing the Impact of Changing the Model
  19. Augmented Designs
    1. A D-Optimal Augmentation of the Reactor Example
      1. Analyze the Augmented Design
    2. Creating an Augmented Design
      1. Replicate a Design
      2. Add Center Points
      3. Creating a Foldover Design
      4. Adding Axial Points
      5. Adding New Runs and Terms
    3. Special Augment Design Commands
      1. Save the Design (X) Matrix
      2. Modify the Design Criterion (D- or I- Optimality)
      3. Select the Number of Random Starts
      4. Specify the Sphere Radius Value
      5. Disallow Factor Combinations
  20. Prospective Sample Size and Power
    1. Launching the Sample Size and Power Platform
    2. One-Sample and Two-Sample Means
      1. Single-Sample Mean
      2. Sample Size and Power Animation for One Mean
      3. Two-Sample Means
    3. k-Sample Means
    4. One Sample Standard Deviation
      1. One Sample Standard Deviation Example
    5. One-Sample and Two-Sample Proportions
      1. One Sample Proportion
      2. Two Sample Proportions
    6. Counts per Unit
      1. Counts per Unit Example
    7. Sigma Quality Level
      1. Sigma Quality Level Example
      2. Number of Defects Computation Example
    8. Reliability Test Plan and Demonstration
      1. Reliability Test Plan
      2. Reliability Demonstration
  21. References
  22. Index

Product information

  • Title: JMP 10 Design of Experiments Guide
  • Author(s):
  • Release date: March 2012
  • Publisher(s): SAS Institute
  • ISBN: 9781612902180