Volume:19 | Number: 4 | July - Aug 2019
Dear Experimenter,
Here’s a fresh set of answers to frequently asked questions (FAQs) about design of experiments (DOE); plus timely alerts for events, publications and software updates. Check it out!
- Mark
Blogs
StatsMadeEasy Blog
(My wry look at all things statistical and/or scientific with an engineering perspective) Also, see the Stat-Ease blog for tips on making DOE easy. For example, a recent posting provides “Four Tips for Graduate Students' Research Projects”. Check it out! 
Alerts
Topics in the body text of this DOE FAQ Alert are headlined below (the “Expert” ones, if any, delve into statistical details):
  1. Website Alert: New look and feel provides much improved browsing experience!
  2. FAQ: How can I convince colleagues working on formulations to use mixture design rather than factorials or response surface methods as they would do for process studies?
  3. Events alert: Upcoming presentations overseas and across the USA
  4. Workshop alert: See when and where to learn about DOE—Sign up now before classes fill.

P.S. Quote for the month: Breaking news—Scientific American observes the “scientists are taught to vary one factor at a time” but they advise that a “multifactorial approach could be more reliable”.

(Page down to the end of this e-zine to enjoy the actual quote.)
Website Alert: New look and feel provides much improved browsing experience!
You may have noticed the new logo for Stat-Ease at the outset of this Alert. This can be seen at our home page www.statease.com as well. However, the changes to our website go far beyond the fresh branding: It’s been completely revamped to make your time there far more invigorating and productive. We hope you like it. Please check it out and get back to us with your feedback. Props to Hank—our webmaster, assisted by Mike (IT). Credit for content goes to Greg, Shari, Cathy and Rachel. It takes a team.
FAQ: How can I convince colleagues working on formulations to use mixture design rather than factorials or response surface methods as they would do for process studies?
Original question from a Research Scientist:
“Empowered by the Stat-Ease class on mixture DOE and the use of Design-Expert, I have put these tools to good use for the past couple of years. However, I am having to more and more defend why a mixture design is more appropriate than factorials or response surface methods when experimenting on formulations. Do you have any resources, blogs posts, or real-world data that would better articulate why trying to use a full factorial or central composite design on mixture components is not the most effective option?”

Answer from Stat-Ease Consultant Martin Bezener:
“First, I assume you are talking about factorials or response surface method (RSM) designs involving the proportions of the components. It makes no sense to use a factorial or RSM if you are dealing with amounts, since doubling the amount of everything should not affect the response, but it will in a factorial or response-surface model.

"There are some major issues with factorial designs. For one thing, the upper bounds of all the components need to sum to less than 1. For example, let’s say you experimented on three components with the following ranges:
A. X1: 10 - 20%
B. X2: 5 - 6%
C. X3: 10 - 90%
then the full-factorial design would lay out a run at all-maximum levels, which makes no sense as that gives a total of 116% (20+6+90). Oftentimes people get away with this because there is a filler component (like water) that takes the formulation to a fixed total of 100%, but this doesn't always happen.

"Also, a factorial design will only consider the extreme combinations (lows/highs) of the mixture. So, you'll get tons of vertices but no points in the interior of the space. This is a waste of resources, since a factorial design doesn't allow fitting anything beyond an interaction model.

"An RSM design can be ‘crammed’ into mixture space to allow curvature fits, but this is generally a very poor design choice. Using ratios of components provides a work-around, but that has its own problems.

"Whenever you try to make the problem fit the design (rather than the other way around), you lose valuable information. A very nice illustration of this was provided in the by Mark Anderson in his article on the 'Peril of Parts & the Failure of Fillers as Excuses to Dodge Mixture Design' in the May 2013 Stat-Teaser.

P.S. The “problems” Martin refers to for using ratios (tedious math!) are detailed in RSM Simplified Chapter 11: “Applying RSM to Mixtures”. You can purchase this book and the others in the Simplified series (“DOE” and “Formulation”) on this page.

(Learn more about mixture design by attending the computer-intensive three-day workshop Mixture and Combined Designs for Optimal Formulations. Click the title for a description of this class and registration details.)
Events alert: Upcoming presentations overseas and across the USA
Stat-Ease Consultant Pat Whitcomb will be kept busy in Budapest briefing the European Network for Business and Industrial Statistics (ENBIS) at their 2019 in Hungary, September 2–4. Not only will he be greeting participants at the Stat-Ease exhibit, Pat also will brief them on “What I’ve Learned about Using Logistic Regression in Conjunction with Design of Experiments” as well as “What's New and Exciting in Design-Expert® Software Version 12”. Plus, Pat will be on the invited panel discussion on big data, open challenges, future of industrial statistics, etc.” led by Editor-in-Chief Marcus Perry of the journal Quality Engineering. For details on ENBIS 19, click here.

Consultant Shari Kraber will represent Stat-Ease as a sponsor of the International Statistical Engineering Association (ISEA) at their Fall Summit in Gaithersburg, Maryland (Washington, DC metro area) September 23-24. Follow this link for information on ISEA’s mission and their conference.

Stat-Ease Consultant Martin Bezener will also be traveling to Gaithersburg to present a 1-day workshop on “Practical DOE: Tricks of the Trade” on September 25 as a lead-in to the two-day Fall Technical Conference (FTC) convening on September 26–27. After working with the ISEA board of directors following their Summit, Shari will join Martin at FTC to exhibit Stat-Ease software. Martin will present a talk on “Practical Aspects of DOE for Binary Data”.

Marketing Manager Greg Campbell, accompanied by various Consultants, will exhibit Stat-Ease software at the Medical Design & Manufacturing (MD&M) Expo in Minneapolis on October 23-24. Please stop by to visit.

Click here for these and other upcoming appearances by Stat-Ease professionals.

P.S. Do you need a speaker on DOE for a learning session within your company or technical society at regional, national, or even international levels? If so, contact me. It may not cost you anything if Stat-Ease has a consultant close by, or if a web conference will be suitable. However, for presentations involving travel, we appreciate reimbursement for travel expenses. In any case, it never hurts to ask Stat-Ease for a speaker on this topic.
Workshop alert: See when and where to learn about DOE—Sign up now before classes fill.
You can do no better for quickly advancing your DOE skills than attending a Stat-Ease workshop. Our expert instructors provide you with a lively and extremely informative series of lectures interspersed by valuable hands-on exercises. Enroll at least 6 weeks prior to the date so your place can be assured—plus get a 10% “early-bird” discount.

Experiment Design Made Easy (EDME)
     October 15-16, Cleveland, OH
     November 21-22, Sarajevo, Bosnia-Herzegovina
     December 3-4, Minneapolis, MN
Modern DOE for Process Optimization (MDOE)
     October 15-17, Cleveland, OH
     December 3–5, Minneapolis, MN
Mixture and Combined Designs for Optimal Formulations (MIXC)
     October 22-24, Edison, NJ

See this web page for complete schedule and site information on all Stat-Ease workshops open to the public. To enroll, scroll down to the workshop of your choice and click on it, or email our Lead Client Specialist Rachel Pollack at workshops@statease.com. If spots remain available, bring along several colleagues and take advantage of quantity discounts in tuition. Or, consider bringing in an expert from Stat-Ease to teach a private class at your site.*

*Once you achieve a critical mass of about 6 students, it becomes very economical to sponsor an on-site workshop, which is most convenient and effective for your staff. For a quote, email workshops@statease.com.
I hope you learned something from this issue. Address your general questions and comments to me at: mark@statease.com.

PLEASE DO NOT SEND ME REQUESTS TO SUBSCRIBE OR UNSUBSCRIBE—
FOLLOW THE INSTRUCTIONS AT THE END OF THIS MESSAGE.

Sincerely,
   Mark

Mark J. Anderson, PE, CQE
Principal, Stat-Ease, Inc.

"Make the most from every experiment!"
Multifactorial "design-of-experiment" (DoE) approach is not new. It was initially developed in the 1920s by statistician Ronald A. Fisher to help optimize crop growth but has rarely been used for biological investigations since then. It is telling, however, that the Food and Drug Administration asks for multifactorial investigations of pharmaceutical production processes to make sure they are consistent when lives rely on reproducible biology, then we insist that scientists use methods that provide true, robust understanding.
  — Markus Gershater and Adam Tozer, Scientific American blog,
Trademarks: Stat-Ease, Design-Expert and Statistics Made Easy are registered trademarks of Stat-Ease, Inc.

Acknowledgements to contributors:
  • Students of Stat-Ease training and users of Stat-Ease software
  • Stat-Ease consultants: Pat Whitcomb, Martin Bezener, and Shari Kraber
  • Stat-Ease programmers: Hank Anderson, Joe Carriere, and Mike Brownson
  • Stat-Ease business staff—Cathy Hickman, Greg Campbell, and Rachel Pollack—who provide such supreme support!
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