Experiment Design Made Easy


Identify the Vital Few Effects—Make Breakthrough Improvements

In this 2-day workshop, find out how to identify your critical quality characteristics using powerful design of experiments (DOE) techniques. Two-level factorial designs keep things simple for finding which factors you need to focus on. Discover previously unknown interactions that often prove to be the key to success. Learn how to use powerful ANOVA analysis methods that give you confidence in your findings.

Apply Tried and True Techniques

Experiment Design Made Easy covers the practical aspects of DOE. (Students may purchase the optional "DOE Simplified" book for reference.) During this introductory DOE workshop, you will discover how to effectively:

  • Understand the motivation for factorial designs
  • Implement the DOE planning process
  • Interpret analysis of variance (ANOVA)
  • Discover hidden interactions
  • Capitalize on efficient fractional designs for screening or characterization
  • Use power to properly size designs
  • Determine when to use transformations
  • Explore multilevel categoric factors
  • Set up split-plot designs
  • Follow the strategy of experimentation from screening to response surface methods
"Practical. Good mix of theory and application." —Chris Easter, Metallurgist

Simulations Provide Practice

Use Design-Expert® software to practice designing and analyzing experiments throughout the workshop. The software has an intuitive top-down and left to right interface for analysis. It provides easy-to-use graphical tools to identify key variables and view results.

"Gives you the 'hands-on' that puts it all together." —Matt Hanken, Senior Manufacturing Engineer

Day 1

Section 1—Introduction to Factorial Design

  • Background and motivation for factorial designs
  • Factorial design planning process
  • Factorial design: Case study
    • Selecting effects—Half-normal plot and Pareto chart
    • ANOVA and residual diagnostics
    • Main effects, interaction, contour and 3D surface plots
    • Introduction to multiple-response optimization

Section 2—Enhancements for Design and Analysis of Factorials

  • Replicated 2^3 full factorial: Case study
    • Explanation of power
  • 2^4 full factorial: Exercise
  • Transformations: Case study
    • Dangers of deleting outliers
    • Details of using transformations

Section 3—Blocking and Fractionating Factorials

  • How to set up optimal blocking: Case study
    • Factors interacting vs three-factor interactions (3FIs)
  • How to set up fractional factorials
  • Understanding aliases
  • 2^5-1 fractional factorial: Exercise

Day 2

Section 4—Small Factorial Designs

  • Minimum-run characterization (MR5) design: Case study
    • Dealing with a low power response
  • Minimum-run screening (MR4) design: Case study
  • Definitive screening (DSD) design
  • Guide to using small-run designs

Section 5—Multilevel Categoric Design

  • Multilevel categoric design: Case study
  • Fractionating via optimal (custom) design: Case study
    • Introduction to optimal (custom) design
    • Model graphs for multilevel categoric designs

Section 6—Split-Plot Designs

  • Restricting randomization
  • Split-plot design: Case study

Section 7—Factorial with Center Points and RSM Introduction

  • Factorial with center points: Case study
  • Introducing response surface methods (RSM)
  • Augmenting to central composite design (CCD): Case study

Knowledge of basic statistics (mean and standard deviation), and exposure to simple comparative experiments (e.g. two-sample t-test) are recommended. To refresh these skills and review basic concepts and terminology, please take the online PreDOE course prior to the workshop. It takes 2-3 hours to complete. You can work at your own pace. Access the PreDOE here.

If you do not complete the PreDOE, and are not familiar with Design-Expert software, then please download a trial of Design-Expert software (if you do not already have access to it) and work through the first tutorial: One Factor - Bowling, found in the Help system.

PDHs: 16 (equals 1.6 CEUs)

Workshop location details will be provided with your confirmation letter, which you will receive once the minimum enrollment requirements are met.

Recommended Texts and Software

Purchase the recommended text or software at the time of registration to receive a 20% discount.

This class is available as a private on-site workshop.

Request a quote today - call our Lead Client Specialist at 612.746.2030 or e-mail workshops@statease.com.

Public Workshops

2019

Experiment Design Made Easy
Minneapolis, MN
December 3 - 4

2020

Experiment Design Made Easy
San Diego, CA
January 28 - 29
Experiment Design Made Easy
Austin, TX
March 9 - 10
Experiment Design Made Easy
Edison, NJ
May 12 - 13
Experiment Design Made Easy
Minneapolis, MN
July 28 - 29
Experiment Design Made Easy
San Jose, CA
October 26 - 27
Experiment Design Made Easy
Minneapolis, MN
December 8 - 9