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If this newsletter prompts you to ask your own questions about DOE, please address them via e-mail to: [email protected].
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PS. Quote for the month: A Nobel Prize-winning philosopher/mathematician provides pithy comments on testing assertions with observational data and listening to data when they speak. (Page down to the end of this e-zine to enjoy the actual quote.) |
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Original Question: From a Lean Six Sigma specialist: Answer: From Stat-Ease Consultant Wayne Adams: Further comments: The semifold will clear up the resolution problem. For more details, see our white paper showing How To Save Runs, Yet Reveal Breakthrough Interactions, By Doing Only A Semifoldover On Medium-Resolution Screening Designs. —Mark (Learn more about two-level factorial design 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.)
Original Question: From a Malaysian chemical-engineering graduate student: Answer: From Stat-Ease Consultant Shari Kraber: Standard error plot for CCD with center points removed In future experiments, we strongly advise staying with the software defaults advised by Design-Expert, which in this case of three factors, calls for 6 center points.”
Original Question: From a industrial statistician working on coatings: Screen shot of logit transformation option This works very well and makes much more sense from a practical standpoint even though the model properties generally get slightly worse. However, it often occurs that the upper limit (or lower limit) of our scale is one of the scores in the experiment, and so we cannot enter those as upper limit (or lower limit) in the logit transformation. What I typically do is add 0.05 to the upper limit of our scale (or subtract 0.05 from our lower limit of the scale) and that works fine. One my colleagues showed that it can make quite a difference what value you add (the 0.05 or something else) in regards to R-squared and other model attributes. So the question is what should I add (or subtract) from theoretical bounds on the upper (or lower) for logit transformation—given these extenuating circumstances? Answer: From Stat-Ease Consultant Pat Whitcomb:
Table of logit transformations with a series of increasing deltas To simplify the comparison I centered the ordinal scale of 1 to 10 on zero by subtracting 5.5 from each value (series 1). Series 2, 3 and 4 are the logit transform with ds of 0.01, 0.1 and 0.5: Graph of logit transformations with a series of increasing deltas As can be seen in the above graph smaller values of d translate into the boundaries being more difficult to approach. One way to choose d is to base it on the expected response behavior: If it is exponentially difficult to approach the boundaries, then use a small d (e.g. 0.01). If the approach is more linear, then use a larger value (e.g. 0.5).”
Check out the white Paper posted on “Using DOE with Tolerance Intervals to Verify Specifications” posted here. It’s based on a talk given by Pat Whitcomb to the 11th annual meeting of the European Network for Business and Industrial Statistics (ENBIS) at the University of Coimbra (Portugal) last September. The tools are geared to the Quality by Design (QbD) initiative by the U.S. Food and Drug Administration (FDA). However, they can just as well be applied to transform how any products are discovered, developed, and manufactured. Rick Caldwell emailed Stat-Ease an alert about publishing this article on “Applying Statistical Design of Experiments to VAE-Based Coatings Development A Formulator’s Perspective” in PCI Magazine. He aimed this at chemists—advising them of the advantages for using DoE instead of one factor at a time (OFAT).
“My daughter’s high school teaches statistics. Most schools cannot afford the full license to your software. I passed along the DOE Simplified flyer to the stats teacher. He was ecstatic to see this economical book including a 180-day license to Design-Ease software. Teachers can get such budgeting through their administration and thus use the program in lessons.” (Fitting coming from a fellow named “Doe”! —Mark) Response Surface Methods (RSM) can lead you to the peak of process performance. In this advanced-level webinar presented on Wednesday, May 23 at 2:00 PM CT,* Stat-Ease Consultant Pat Whitcomb will discuss robust design, propagation of error, and tolerance analysis. Propagation of error (POE) accounts for variation transmitted from deviations in factor levels. It finds the flats—high plateaus or broad valleys of response, whichever direction one wants to go—maximum or minimum; respectively. Tolerance analysis drills down to the variation of individual units, thus facilitating improvement of process capability. 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!)
You are invited to participate in our Fourth European Design of Experiments (DOE) User Meeting in Vienna, Austria. Find all the details here. The meeting will focus on DOE, with a special emphasis on Design-Expert software. Both the theoretical and practical aspects of DOE will be addressed, including the latest developments in the field. The two meeting days will include lectures by DOE experts, case study presentations by DOE practitioners, and an opportunity to consult with the experts about your DOE applications. Optional pre-meeting workshops will be presented to sharpen these powerful statistical tools. Oh, and let’s not overlook the opportunity for breaking away to spend time in Vienna—a magnificent city of world culture.
Pat Whitcomb jets halfway around the world to present a one-day workshop on DOE for QbD to pharma researchers in India. See all the details here. Stat-Ease will exhibit at the 2012 American Association of Pharmaceutical Scientists (AAPS) National Biotechnology Conference in San Diego, CA, on May 21-23 (Booth N313). Shari Kraber will provide a lecture for the post-conference short course on Practical Essentials of Design of Experiments (DoE) toward Robust Bioanalysis on May 24. See the details here. See Stat-Ease also at the 29th Quality and Productivity Research Conference in Long Beach, CA, June 4-7. Wayne Adams will provide a demo of Design-Expert software on June 6th, 3-4 pm. PS. 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. |
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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 EDME and RSM in February to earn $395 off the combined tuition!
** Take both MIX and MIX2 to earn $395 off the combined tuition!
Mark Mark J. Anderson, PE, CQE
For breaking news from Stat-Ease go to this Twitter site. DOE FAQ Alert ©2012 Stat-Ease, Inc. |
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