Modern DOE for Process Optimization

Use State-of-the-Art DOE Tools to Make Breakthrough Improvements and Optimize the Final Results

This 3-day workshop on factorial and response surface methods combines the topics and brings new insights into one fast-paced course! Find out how to make breakthrough improvements using powerful design of experiments (DOE) techniques. Start by learning about using factorial designs 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 best use modern small-run designs to save time and money experimenting. Transition from factorials to response surface methods to optimize your products and processes. Tie all of this together by learning how to use powerful ANOVA analysis methods that give you confidence in your findings.

Apply Tried and True Techniques

This workshop covers the practical aspects of DOE. (Students may purchase the optional "DOE Simplified" book for reference.) You learn all about simple but powerful two-level factorial designs. During this 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 small-run fractional designs for screening or characterization
  • Use power to properly size designs
  • Determine when to use transformations
  • Explore multilevel categoric factors
  • Set up modern split-plot designs - both factorial and RSM
  • Follow the strategy of experimentation from screening to response surface methods
  • Set up central composite (CCD), Box-Behnken and Optimal RSM designs
  • Select appropriate regression models
  • Optimize multiple responses numerically
  • Add multilinear constraints and categoric factors to optimal designs
"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 provides easy-to-use graphical tools to find key variables and view results. You will be given all simulation and data files used in class, along with a free fully-functional, but time-limited, copy of Design-Expert software for use after class.

"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

Day 3

Section 1—Response Surface Methods - Central Composite Designs

  • "Good" response surface designs
  • Response surface methods: Case study
    • Differences: response surface vs factorial
      • Sizing for precision
      • RSM analysis
  • Model reduction exercise

Section 2—Response Surface Optimization and Confirmation

  • Optimization exercise
    • Numerical
    • Graphical
    • Adding a cost equation
  • Exercise with multiple responses

Section 3—Response Surface Designs

  • Box-Behnken design: Case study
  • Face-centered CCD (FCD)
    • Design Evaluation
    • Exercise

Section 4—Optimal Design

  • Multiple linear constraints (MLCs): Case study
    • Optimal designs
  • Categoric factors: Case study
  • RSM design summary

Section 5—Mixture Overview and Next Steps

  • Mixture design overview: Case study
  • Exercise: optimize your process
  • Next steps

Section 6—Appendix: Split-Plot Design for RSM (as time allows)

  • Review split-plot concept
  • Central composite split plot: Case study
  • Optimal three-level split plot: 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: 24 (equals 2.4 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.

Host this class at your company!

Request a quote today - call our Lead Client Specialist at 612.378.9449 or email

Public Workshops


Modern DOE for Process Optimization (IPL)

Optimize your processes by mastering factorial and response surface designs in this 2.5-day in-person course. 

Regular price $1295.

Minneapolis, MN
October 5 - 7