dxDOE design of experiment for students.ppt

Text on statistics which can be used by students and professionals. This covers more topics which are relevant to professionals in the field who need the knowledge"

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1. “How To Design Your
Model”

2. DOE Software
Design of Experiment
www.statease.com
ThisEASYTOUSEsoftwarehasallthemajor
experimentaldesigns(generalANOVA,two-levelfull
andfractionalfactorials,three-levelfactorials,several
RSMdesigns,mixturedesigns,andmuchmore).
Moreandmorefeaturesareaddedwitheachnew
versionofthesoftware.
Ithaspowerfulgraphicaltoolsandithasbeen
featuredinseveralwell-knowntextsonDOE.
ApparentlyithasbeenWIDELYUSEDIN
INDUSTRY.
ThewebsiteprovidesexcellentDOEresourcesand
onecandownloada30-dayfullversionfromthe
website.

3. ThissoftwarealsoclaimsthatitoffersPRACTICALITY
andEASE-OF-USEthatisIDEALFORBEGINNERS
butwiththecomputingpowerdemandedbyadvanced
users.
ItbasicallyoffersVERYSIMILARFEATURESTO
DESIGN-EXPERTwiththeadditionoftheParetochart
andafewotherminordifferences.
OnecanDOWNLOAD A15-DAYFULLVERSIONof
the
softwareforthewebsite.
DOE Wisdom
www.launsby.co
DOEpack
www.pqsystems.com
Thisstandalonesoftwareavailablealso
FEATURES THEUSUALCLASSICAL AND
TAGUCHIDESIGNSwithawideselectionof
SCREENING DESIGNS, PROCESS
OPTIMIZATION DESIGN ANDANALYSIS
TOOLS.
Ithasgoodgraphicaltoolsandanintuitiveuser
interface

4. ThisstandaloneDOEsoftwareisdevelopedbythe
well-knownSASInstitute,developersoftheSAS
program.
Thisisalsopowerfulsoftwareandprovidesdesign
choicesforalmosteverysituation.Perhapsthe
additionalfeaturethatisnotavailableintheother
softwareisthattheusercanperformcustomdesigns
whichgivetheexperimenterthemostflexibility.
Obviously,thisfeatureisONLYUSEFULFORTHE
EXPERTUSER.Limitedtimefreedownloadofthe
softwareisalsoavailablefromtheJMPwebsite.
www.jmp.com

5. Design Expert Version 7.1.5 or LATEST Version 8

6. Doe Vocabulary
Factor One of the independent variables under investigation that
can be set to desire value
K Number of factors or variables the effect of which are to be
estimated in an experimental
Level The numerical value or qualitative feature of a factor
Run The act of operating the process with a factors at certain
setting
Response The numerical result of a run
FactorExperiment Design to determine the effect of all possible combinations
acrossall level of the factor under study
Factorial Factorial Designed to examinek factors with the fraction of the runs
required for a full factorial
Blocking Astrategy for designing experiment to provide the ability to
eliminate from the experimental error a contributor of
variability that is known but not under investigation

7. Why Goes For
Experimental Design?
EFFICIENCYGet
more info from fewer
experiments
FOCUSINGCollect
only info that really
needed
is a useful complement to multivariate data analysis.
with designed experiments there is a better possibility of
testing the significance of the effects and the relevance
of the whole model .
1 2

8. DOE Flowchart?
Set your
objective
Select Output
Response
Select Input
Factors
Select your
design
Develop your
strategy
Run
Experiment
Fit & Diagnose
Model
Interpret
Model
Confirm
Model
1
3
2
4
5
6
7
8
9
Will be
explain
next
semester

9. Building a Experimental
Design !
DEFINE THE OBJECTIVEof
the investigation: e.g. “sort out
important variables” or “find
the optimum conditions
1
Toscreenandidentifythe
POTENTIAL PLANT
PARTSofPROTEASE
PRODUCTION from
StreblusasperbyusingDesign
ofExperiment(DOE).
Example:
Studies Of Potential Parts Of Streblus
asper (Kesinai) For Protease Production
Your Final Year Project Titles

10. Building a Experimental
Design !
SELECT INPUT
FACTORS
that will be
controlled during
the experiment
(design variables),
and their levels or
ranges of
variation.
2 Weight of your
sample (g)
Ratio (mol)
(Buffer : Sample)
Time of Extraction
(minutes)
SELECT
OUTPUT
RESPONSE
that will be
measured to
describe the
outcome of the
experimental
runs (response
variables), and
examine their
precision
3
Enzyme
Activity
(unit/mL)

11. Building a Experimental
Design !
SELECT YOUR DESIGN
CHOOSEamong the available
standard designsthe one that is
compatible with the objective,
number of design variables and
precision of measurements, and
has a reasonable cost
4

12. ScreeningDesign
TheScreeningdesignersuppliesa
listofpopularscreeningdesigns
for2ormorefactors.
Screeningfactorscanbe
continuousorcategoricalwithtwo
orthreelevels.
Thelistofscreeningdesignsalso
includesdesignsthatgroupthe
experimentalrunsintoblocksof
equalsizeswherethesizeisa
poweroftwo.

13. WELCOME! 1

14. START YOUR DESIGN!!2

15. Choose
The
Experimental
Design
3
4

16. Theotherchoicesare
coloredlikeastoplight:
GREEN FORGO,
YELLOW FOR
PROCEED WITH
CAUTION,andRED
FORSTOP,which
represent varying
degreesofresolution:≥
V,IV,andIII,
respectively.
This design builder
offers full and
fractional two‐level
factorials for 2 to 21
factors
in powers of two (4, 8,
16…) for up to 512
runs.
Thechoicesappearincoloronyourscreen.White
squaressymbolizefullfactorialsrequiring2k
runsfork(thenumberoffactors)from2
to9.
Foraquickoverviewofthesecolorcodes,pressthescreen
tipsbutton(orselectTips,ScreenTips)andclick
topic1:“Whattypeofinformationdoyouwant?”

17. 7Insert your factors and unit
8
Insert your range here!
Make sure the range is not
too small or too big
9

18. Factors
Numeric
Temperature
Pressure
Categoric
Catalyst
Type
Automotive
Model

19. 11Insert your response here!
10
Choose number of response in your
study
12

20. 13
List of experiment that you design before will be
shown here
14
Insert your
experimental
data here
Develop your
strategy
Run
Experiment
5
6
Actual
Values!!!!

21. 15
You might choose process factors in coded or actual

22. You’veputinsomeworkatthispointsoitisagoodtimetosaveit.Thequickestwayof
doingthisistopressthestandardsaveicon.ButyoucanalsogototheFilemenuand
selectSaveAs.Typeinthenameofyourchoiceforyourdatafile.
ThenclickSave.

23. ForPlackettBurman Design
minimumfactoris11.
Ifyourfactorsislessthan11,you
adddummiesfactorstocomplete
it.
Nextstepisthesameasprevious.

24. ResponseSurfaceDesign
ResponseSurfaceMethodology(RSM)isan
experimentaltechniqueinventedtofindtheoptimal
responsewithinthespecifiedrangesofthefactors.
Thesedesignsarecapableoffittingasecondorder
predictionequationfortheresponse.
Thequadratictermsintheseequationsmodelthe
curvatureinthetrueresponsefunction.Ifamaximum
orminimumexistsinsidethefactorregion,RSMcan
findit.
Inindustrialapplications,RSMdesignsinvolveasmall
numberoffactors.Thisisbecausetherequirednumber
ofrunsincreasesdramaticallywiththenumberof
factors.TheResponseSurfacedesignerinJMPlists
well-knownRSMdesignsfortwotoeightcontinuous
factors.Someofthesedesignsalsoallowblocking

25. Axial(orstar)points,forwhichallbutonefactorsetatzero
(midrange)andonefactorsetatouter(axial)values.
One distinguishing feature of the Box-Behnken design is that there are ONLY THREE
LEVELS PER FACTOR.
Another important difference between the two design types is that theBOX-
BEHNKEN DESIGN HAS NO POINTS AT THE VERTICES OF THE
CUBEdefined by the ranges of the factors.
This is sometimes useful when it is desirable to avoid these points due to engineering
considerations. The price of this characteristic is the higher uncertainty of prediction near
the vertices compared to the Central Composite design.
CENTRALCOMPOSITE design,combinesatwo-levelfractionalfactorialandtwo
otherkindsofpoints:
Centerpoints,forwhichallthefactorvaluesareatthezero
(ormidrange)value.
Fractional
factorial
point
Axial
Point
Centre
Point
TheBOX-BEHNKENdesign, is an alternative to central composite designs.

26. Insert your optimize factor and your
range here
1
2
Number of run

27. Insert list of response involved in your optimization here
3

28. Actual Values!!!!
4
List of experiment that you design before will be
shown here
5
Insert your
experimental
data here
Develop your
strategy
Run
Experiment
5
6

29. Thank you…..