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The Successful Application
 of Designed Experiments
Carl D. McAfee, Ph.D.
McAfee Consulting LLC
27 September 2005
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Objectives of this talk:
nProvide a general introduction to the concept and a basis for selecting an appropr= iate designed experiment for your application nProvid= e a broad understanding of the wide array of options for using designed expts nProvide a few examples of the process from beginning to end
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Designed Experiments
nAre a series of experiments where several factors are changed simultaneously a= nd responses are measured and analyzed for their statistical significance nAre an efficient way to experiment and obtain meaningful data and mathematical models for better decision making = = nAre no= t a substitute for subject matter knowledge and common sense=
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Platforms that exist to use DOE
nSimple enough to do calculations by hand
nSeveral software packages that are available to make the concept easier = to use
nDesign-Expert, Minitab, JMP, SAS, etc.
nMost of the statistical calculations are basic statistics with algebra as the calculating piece
nMost of the software packages do the math for you, but an understand= ing of the concept is most helpful in interpreting your data=
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Basic Statistics that are useful in DOE
<= span class=3DBB style=3D'position:absolute;left:-4.61%;top:.1em'>nAverag= e
<= span class=3DBB style=3D'position:absolute;left:-4.61%;top:.1em'>nStanda= rd Deviation
<= span class=3DBB style=3D'position:absolute;left:-3.89%;top:.1em'>nF-stat= istic (F value at a given confidence level)
<= span class=3DBB style=3D'position:absolute;left:-4.61%;top:.1em'>nAnalys= is of Variance (ANOVA)
<= span class=3DBB style=3D'position:absolute;left:-4.61%;top:.1em'>nRegres= sion Analysis (R squared)
<= span class=3DBB style=3D'position:absolute;left:-4.53%;top:.1em'>nLinear equations (linear, quadratic, etc.)
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A Strategy for Experimentation
nConsid= er your experimental budget
nChose = an appropriate design
n<= /span>Don’t use more than 25% of your budget on your first design
nPerfor= m your experiment
nAnalyz= e your results
<= span class=3DBB style=3D'position:absolute;left:-4.35%;top:.1em'>nDeterm= ine the significance of your results
nConsid= er an optimization design to select the best set of operating conditions/factor settings
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Different Types of Designs
nFactorials
nGeneral, Two Level, Fractional, Irregular
nResponse Surface Methods
nCentral Composite, Box Behnken, D-Optimal
nMixtures
nSimplex, Centroid
nOthers
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Advantages of Factorial Designs
nNumber= of runs are minimized
nReplic= ation is built-in
nGives = more information than OFAT
nKey Interactions are observed !
nEasy to analyse and interpret
nFactor= ials are the beginnings of RSMs
n
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Lets Look at a couple of examples
nConsider the factors that influence the filtrate in a pilot plant scale-up of= a process
nFiltrate.dx6
nConsider the factors that influence the shrinkage of a part in an injection molding operation
nInjection.dx6
nConsider the factors that influence the yield of a reaction for a given product in yo= ur company
nYield.dx6
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What information should we consider?
<= span class=3DBB style=3D'position:absolute;left:-3.87%;top:.1em'>nWhich = effects are significant and which are not
<= span class=3DBB style=3D'position:absolute;left:-4.57%;top:.1em'>nIs the= entire data set valid?
<= span class=3DBB style=3D'position:absolute;left:-4.08%;top:.1em'>nWhat d= oes the mathematical model look like
<= span class=3DBB style=3D'position:absolute;left:-3.82%;top:.1em'>nWhat d= oes the error structure of the data tell us
nCan I = make interpretations from the model?
n<= /span>Where should I set the factors to give a best operating condition
<= span class=3DBB style=3D'position:absolute;left:-3.92%;top:.1em'>nDo I n= eed to consider additional experiments?
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Conclusions & Observations
nDesign= ed experimentation is a valid approach
n<= /span>The results give statistical significance and confidence in the decision making process nFrom an efficiency perspective we are much more efficient in our experiments as compared to one-factor-at-a-time (OFAT) nWe generate model= s that are useful over and over again
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Refere= nces & Sources for further study
nBest textbook
nDesign & Analysis of Experiments, 5th=  edition
nby Douglas Montgomery
nBest software
nDesign-Expert Version 6 by Stat-Ease, Inc.
nBest course
nThe one you will attend, attend several
nBest website
nwww.statease.com
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Contact Information:
nCarl D. McAfee, Ph.D.
nMcAfee Consulting LLC
nP.O. Box 36, Kennedale, TX 76060
n= cmcafee@prochemist.com
nOffice: 817.483.4126
nFax: 817.483.7574
nMobile: 817.235.8817
n
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