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Learn About JMP

Contents

JMP Design of Experiments

1 Learn About JMP

Documentation and Additional Resources

Book Conventions

JMP Documentation

JMP Documentation Suite

JMP Help

JMP Books by Users

JMPer Cable

Additional Resources for Learning JMP

Tutorials

The JMP Starter Window

Sample Data Tables

Learn about Statistical and JSL Terms

Learn JMP Tips and Tricks

Tooltips

Access Resources on the Web

2 Introduction to Designing Experiments

A Beginner’s Tutorial

About Designing Experiments

My First Experiment

The Situation

Step 1: Design the Experiment

Step 2: Define Factor Constraints

Step 3: Add Interaction Terms

Step 4: Determine the Number of Runs

Step 5: Check the Design

Step 6: Gather and Enter the Data

Step 7: Analyze the Results

3 Examples Using the Custom Designer

Creating Screening Experiments

Creating a Main-Effects-Only Screening Design

Creating a Screening Design to Fit All Two-Factor Interactions

A Compromise Design Between Main Effects Only and All Interactions

Creating ‘Super’ Screening Designs

Screening Designs with Flexible Block Sizes

Checking for Curvature Using One Extra Run

Creating Response Surface Experiments

Exploring the Prediction Variance Surface

Introducing I-Optimal Designs for Response Surface Modeling

A Three-Factor Response Surface Design

Response Surface with a Blocking Factor

Creating Mixture Experiments

Mixtures Having Nonmixture Factors

Experiments that are Mixtures of Mixtures

Special Purpose Uses of the Custom Designer

Designing Experiments with Fixed Covariate Factors

Creating a Design with Two Hard-to-Change Factors: Split Plot

Technical Discussion

4 Building Custom Designs

The Basic Steps

Creating a Custom Design

Enter Responses and Factors into the Custom Designer

Describe the Model

Specifying Alias Terms

Select the Number of Runs

Understanding Design Evaluation

Specify Output Options

Make the JMP Design Table

Creating Random Block Designs

Creating Split Plot Designs

Creating Split-Split Plot Designs

Creating Strip Plot Designs

Special Custom Design Commands

Save Responses and Save Factors

Load Responses and Load Factors

Save Constraints and Load Constraints

Set Random Seed: Setting the Number Generator

Simulate Responses

Save X Matrix: Viewing the Number of Rows in the Moments Matrix and the Design Matrix (X) in the Log

Optimality Criterion

Number of Starts: Changing the Number of Random Starts

Sphere Radius: Constraining a Design to a Hypersphere

Disallowed Combinations: Accounting for Factor Level Restrictions

Advanced Options for the Custom Designer

Save Script to Script Window

Assigning Column Properties

Define Low and High Values (DOE Coding) for Columns

Set Columns as Factors for Mixture Experiments

Define Response Column Values

Assign Columns a Design Role

Identify Factor Changes Column Property

How Custom Designs Work: Behind the Scenes

5 Screening Designs

Screening Design Examples

Using Two Continuous Factors and One Categorical Factor

Using Five Continuous Factors

Creating a Screening Design

Enter Responses

Enter Factors

Choose a Design

Display and Modify a Design

Specify Output Options

View the Design Table

Create a Plackett-Burman design

Analysis of Screening Data

Using the Screening Analysis Platform

Using the Fit Model Platform

6 Response Surface Designs

A Box-Behnken Design: The Tennis Ball Example

The Prediction Profiler

A Response Surface Plot (Contour Profiler)

Geometry of a Box-Behnken Design

Creating a Response Surface Design

Enter Responses and Factors

Choose a Design

Specify Output Options

View the Design Table

7 Full Factorial Designs

The Five-Factor Reactor Example

Analyze the Reactor Data

Creating a Factorial Design

Enter Responses and Factors

Select Output Options

Make the Table

8 Mixture Designs

Mixture Design Types

The Optimal Mixture Design

The Simplex Centroid Design

Creating the Design

Simplex Centroid Design Examples

The Simplex Lattice Design

The Extreme Vertices Design

Creating the Design

An Extreme Vertices Example with Range Constraints

An Extreme Vertices Example with Linear Constraints

Extreme Vertices Method: How It Works

The ABCD Design

Creating Ternary Plots

Fitting Mixture Designs

Whole Model Tests and Analysis of Variance Reports

Understanding Response Surface Reports

A Chemical Mixture Example

Create the Design

Analyze the Mixture Model

The Prediction Profiler

The Mixture Profiler

A Ternary Plot of the Mixture Response Surface

9 Discrete Choice Designs

Introduction

Create an Example Choice Experiment

Analyze the Example Choice Experiment

Design a Choice Experiment Using Prior Information

Administer the Survey and Analyze Results

Initial Choice Platform Analysis

Find Unit Cost and Trade Off Costs with the Profiler

10 Space-Filling Designs

Introduction to Space-Filling Designs

Sphere-Packing Designs

Creating a Sphere-Packing Design

Visualizing the Sphere-Packing Design

Latin Hypercube Designs

Creating a Latin Hypercube Design

Visualizing the Latin Hypercube Design

Uniform Designs

Comparing Sphere-Packing, Latin Hypercube, and Uniform Methods

Minimum Potential Designs

Maximum Entropy Designs

Gaussian Process IMSE Optimal Designs

Borehole Model: A Sphere-Packing Example

Create the Sphere-Packing Design for the Borehole Data

Guidelines for the Analysis of Deterministic Data

Results of the Borehole Experiment

11 Accelerated Life Test Designs

Designing Experiments for Accelerated Life Tests

Overview of Accelerated Life Test Designs

Using the ALT Design Platform

Platform Options

Example

12 Nonlinear Designs

Examples of Nonlinear Designs

Using Nonlinear Fit to Find Prior Parameter Estimates

Creating a Nonlinear Design with No Prior Data

Creating a Nonlinear Design

Identify the Response and Factor Column with Formula

Set Up Factors and Parameters in the Nonlinear Design Dialog

Enter the Number of Runs and Preview the Design

Make Table or Augment the Table

Advanced Options for the Nonlinear Designer

13 Taguchi Designs

The Taguchi Design Approach

Taguchi Design Example

Analyze the Data

Creating a Taguchi Design

Detail the Response and Add Factors

Choose Inner and Outer Array Designs

Display Coded Design

Make the Design Table

14 Evaluating Experimental Designs

Using the Evaluate Design Platform

Launching the Evaluate Design Platform

The Evaluate Design Report

Examples

Assessing the Impact of Lost Runs

Assessing the Impact of Changing the Model

15 Augmented Designs

A D-Optimal Augmentation of the Reactor Example

Analyze the Augmented Design

Creating an Augmented Design

Replicate a Design

Add Center Points

Creating a Foldover Design

Adding Axial Points

Adding New Runs and Terms

Special Augment Design Commands

Save the Design (X) Matrix

Modify the Design Criterion (D- or I- Optimality)

Select the Number of Random Starts

Specify the Sphere Radius Value

Disallow Factor Combinations

16 Prospective Sample Size and Power

Launching the Sample Size and Power Platform

One-Sample and Two-Sample Means

Single-Sample Mean

Sample Size and Power Animation for One Mean

Two-Sample Means

k-Sample Means

One Sample Standard Deviation

One Sample Standard Deviation Example

One-Sample and Two-Sample Proportions

One Sample Proportion

Two Sample Proportions

Counts per Unit

Counts per Unit Example

Sigma Quality Level

Sigma Quality Level Example

Number of Defects Computation Example

Reliability Test Plan and Demonstration

Reliability Test Plan

Reliability Demonstration

Index

JMP Design of Experiments

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