## I'm doing Six Sigma or Lean

Design of experiments (DOE) is a very important element in Six Sigma or Lean methodology. Stat-Ease offers a structured statistical approach to help you understand the factors that affect a process and then create meaningful and effective tests to verify possible improvement ideas or theories. We focus on making DOE as easy as possible with relevant articles, top-notch training, consulting services, books, newsletters, FAQs and DOE Resources, and user-friendly software.

#### Best Practices

Stat-Ease offers a several articles on DOE and Six Sigma. If you would like to learn more about this subject, we recommend you begin with the articles below.

1. The Six Sigma Method and Design of Experiments—This article by Peter Peterka (www.6sigma.us) explains what Six Sigma is and DOE's role in it.
2. Cost-Effective and Information-Efficient Robust Design for Optimizing Processes and Accomplishing Six Sigma Objectives—Standard factorial designs (one array) offer a cost-effective and information-efficient robust design alternative to parameter designs (two -array) made popular by Taguchi. This paper compares these two methods (one-array versus two-array) in depth via an industrial case study. It then discusses advanced tools for robust design that involve application of response surface methods (RSM) and measurement of propagation of error (POE). Also see this postscript to the article. (ps_re_Taguchi.pdf—120KB)
3. Six Sigma for the Road—Read this Stat-Teaser newsletter article from Mark Anderson on using propagation of error (POE) and multiple response optimization to analyze a DOE on driving time.

Click here to go the Case Studies page and see all available DOE articles and case studies.

#### Training

The quickest and easiest way to learn design of experiments and incorporating it into your Six Sigma practices is to attend our workshop, Modern DOE for Process Optimization. In this computer-intensive workshop participants set up, analyze, and interpret DOE's ranging from fractional factorials to response surface (RSM) designs. During this 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
• 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

#### Articles

2. Trimming the FAT: Part II—This follow-up article offers a case study that illustrates how a two-level factorial DOE can reveal a breakthrough interaction.
3. Rethink Experiment Design—This is another article on DOE versus the traditional OFAT method.
4. Eight Keys to Successful DOE—Using DOE successfully depends on understanding eight fundamental concepts which are explained in this article.
5. Design of Experiments—A Primer—This article looks at some of the basic DOE concepts that are necessary for practitioners to understand.

Click here to go the Articles page and see all available DOE articles and case studies.

#### Books

Visit the Stat-Ease bookstore for recommended books on DOE. To get you off to a good start we suggest:

DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition, by Anderson & Whitcomb—This updated introductory text covers the basic essentials about factorial DOE. It is filled with interesting anecdotes and sidebars that make it fun to read.

Bring the DOE Simplified, 3rd Edition book to life with it's companion e-learning experience, the DOE Simplified Launchpad. This completely narrated presentation of the first three chapters of the book includes hands-on exercises. It is designed to bring you up to speed on the basics of two-level factorial design. For more information, click here.

RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, 2nd Edition, by Anderson & Whitcomb—This book is the next step in your DOE education. Its simple and fun approach is for those who desire knowledge on response surface methods, but dislike the academic nature of other books on the topic.

This text is now available directly from the publisher or from other book sellers such as Amazon.

#### Webinars

Stat-Ease offers free webinars on a variety of subjects several times during the year. Get more information and register here. Also on that page are listings of past webinars with recordings that you can view at your leisure.