Stat-Ease | The DOE FAQ Alert Vol. 12 No. 1

1: Software Alert: Version 8.0.7 of Design-Expert software released (free update for licensed users of v8)

Newly-released version 8.0.7 of Design-Expert software is posted at this download site for free trial evaluation. This web site also provides free patches to update older licensed versions of 8.0. The release primarily provides maintenance of existing features. View the ReadMe file for details on this update, installation tips, known ‘bugs,’ change history, and FAQs.

PS. Reminder: If you want to receive notice when an update becomes available, go to Edit on the main menu of your program, select Preferences and, within the default General tab, turn on the “Check for updates on program start” option.

2: Newsletter Alert: January issue of the Stat-Teaser features an experiment aimed at developing cookies that taste good despite variations in the time and temperature of baking

Many of you have received, or soon will, a printed copy of the latest Stat-Teaser, but others, by choice or because you reside outside of North America, will get your only view of the January issue at this link. It features an article by me on how “Sophisticated DOE tools produce tasty cookies time after time” for Design For Six Sigma (DFSS) guru Andy Sleeper (Successful Statistics, LLC). It was great that Andy allowed me to share this fun and enlightening case study on the application of POE (propagation of error) tools in Design-Expert software.

This Stat-Teaser also provides a very helpful primer by Consultant Shari Kraber on “Practical Aspects of Algorithmic Design of Physical Experiments, from an Engineer’s Perspective.”

Thank you for reading our newsletter. If you get the hard copy, but find it just as convenient to read what we post to the Internet, consider contacting us to be taken off our mailing list, thus conserving resources. (Note: You will be notified via the DOE FAQ Alert on new newsletter posts.) In any case, we appreciate you passing along hard copies and/or the link to the posting of the Stat-Teaser to your colleagues.

PS. Re baking cookies, check out this riveting video of an MIT robot trying its ‘hand’ at whipping up a batch.

From a Process Engineer:
“Hello! I’m analyzing my first factorial DOE with blocking and center points. I am seeking some feedback on my analysis, and have a few questions:

Since the Block Mean Square value is large compared to the Residual Mean Square value, I am under the impression that the effect of blocking is significant. I am not surprised by this since the process was not running as smoothly on Day 1 as Day 2 for an unknown reason.

I ran three center points per block. The ANOVA analysis reveals that the curvature is significant. Since the curvature MS value is on the same order as the block MS value, is it possible that there is a block-related issue that makes the curvature seem more significant than it really is, or are these effects completely independent in the analysis? Since we encountered some problems with the process on Day 1, the standard deviation of parts measured within individual runs was generally larger on this day. The curvature was significantly less in the second block, with all three points seeming to follow the linear model (on the 2FI graph, they’re between the two lines at the middle value on the x axis).

My interpretation of this situation is that the actual amount of curvature cannot fully be determined at this time due to the behavior of the equipment on Day 1. Since R1 must be minimized, the best conditions are the high level of factor A and the low level of Factor B, even with the curvature. If curvature is as large as suggested by the lower 2 center points on the graph, the implication is that the system is not as sensitive to a slight decrease in Factor A and slight increase in Factor B as the linear model would suggest. The curvature, however, does not significantly impact the selection of optimal factors within this design space.

From Stat-Ease Consultant Wayne Adams:
“Start by looking at the Graph Columns node. This is the data without any adjustments plotted in a scatterplot. Set the X-axis to factor A, the Y Axis to the response and then the color by to block. It appears to me that there is very little block effect and very little curvature.

Color by Block option for Graph Columns node in Design-Expert software (example from workshop)

(Learn more about blocking by attending the two-day computer-intensive workshop Experiment Design Made Easy. Click on the title for a description of this class and link from this page to the course outline and schedule. Then, if you like, enroll online.)

“Design of Experiments for Non-Manufacturing Processes: Benefits, Challenges and Some Examples” by Jiju Antony; Doug Montgomery; Shirley Coleman; myself and Rachel Silvestrini was published in the Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture last November (vol. 225, no. 11, pp 2078-2087). It refers to my white paper on “DOE for Non-Manufacturing”.

5: Webinar Alert: Basics of RSM for process optimization (part 2 of 2)—Encore!

Response Surface Methods (RSM) can lead you to the peak of process performance. In this intermediate-level webinar presented on Wednesday, February 22 at 10:30 AM CT,* Stat-Ease Consultant Brooks Henderson will present a second round of education on response surface methods (RSM) for optimizing processes.

If you are new to RSM, this webinar is for you! If you missed part 1, do not worry—we posted the recorded presentation by Consultant Shari Kraber here.

Stat-Ease webinars vary somewhat in length depending on the presenter and the particular session—mainly due to breaks for questions: Plan for 45 minutes to 1.5 hours, with 1 hour being the target median. When developing these one-hour educational sessions, our presenters often draw valuable material from Stat-Ease DOE workshops.

Attendance may be limited, so sign up soon by contacting our Communications Specialist, Karen Dulski, via [email protected]. If you can be accommodated, she will provide immediate confirmation and, in timely fashion, the link with instructions from our web-conferencing vendor GotoWebinar.

*(To determine the time in your zone of the world, try using this link. We are based in Minneapolis, which appears on the city list that you must manipulate to calculate the time correctly. Evidently, correlating the clock on international communications is even more complicated than statistics! Good luck!)

6: Conference Alert: 4th European DOE Meeting June 27-28 in Vienna—save the date!

Block off the last week of June for the Fourth European Design of Experiments (DOE) User Meeting and Workshops. Watch for details coming on our web site, via the next DOE FAQ Alert and in e-mailed announcements.

7: Events Alert: Statistical conference in Orlando, QbD meeting in Mumbai, and much more

Break away to Orlando, FL on February 16-18 to attend an electronic poster presentation by Consultant Shari Kraber on “Using DOE with Tolerance Intervals” at the inaugural Statistical Practice Conference, sponsored by the American Statistical Association (ASA). For details, click here.

If you work in a defense industry, come to the National Test and Evaluation Conference on March 12-15 at Hilton Head, SC, and hear my talk on “Practical Aspects for Designing Statistically Optimal Experiments.” The sponsor, the National Defense Industrial Association (NDIA), provides information on this “T&E” technical meeting at this link.

Shari returns to Minnesota in April (actually sooner—we hope) for the 1st Annual Professional Development Summit held in Brooklyn Center on April 2-3. She will present a talk on the “Top Ten Modern-Day Statistical Tools for Quality Professionals.” See details posted on the Summit at this site posted by the Minnesota Section of the American Society of Quality (ASQ)—the sponsor.

Stat-Ease Consultant Pat Whitcomb travels halfway around the world to give a workshop on DOE for QbD at the Quality by Design India 2012 conference in Mumbai, India on April 11-13. It is affiliated with CPhI India—an annual event for API, generics, fine chemicals and bio-pharmaceuticals industries in the subcontinent. For more information contact Stat-Ease.

Back here in the States, Stat-Ease will exhibit to members of the American Association of Pharmaceutical Scientists (AAPS) who attend the 2012 National Biotechnology Conference in San Francisco on May 21-23. Register here for the post-conference Short Course on “Practical Essentials of Design of Experiments (DoE) toward Robust Bioanalysis,” where Shari will provide an “Introduction to Design-Expert for DOE Analysis.”

Down the California coast a few weeks later, June 4-7, you can see Design-Expert software demonstrated by Consultant Wayne Adams for the 29th Quality and Productivity Research Conference. While there, attend a new talk by Pat Whitcomb on “How to Design Experiments when Categoric Mixture Components Go to Zero.” Click here for more details and link to the conference flyer.

Seats are filling fast for the following DOE classes. If possible, enroll at least 4 weeks prior to the date so your place can be assured. However, do not hesitate to ask whether seats remain on classes that are fast approaching! Also, take advantage of a $395 discount when you take two complementary workshops that are offered on consecutive days.

All classes listed below will be held at the Stat-Ease training center in Minneapolis unless otherwise noted.

*** Take both MIX and MIX2 to earn $395 off the combined tuition!

See this web page for complete schedule and site information on all Stat-Ease workshops open to the public. To enroll, click the "register online" link on our web site or call Elicia at 612-746-2038. 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 a private workshop, which is most convenient and effective for your staff. For a quote, e-mail [email protected].