Design and Analysis of MultiFactored Experiments. Fractional Factorial Designs. Design of Engineering Experiments – The 2 kp Fractional Factorial Design.
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For the principal fraction, notice that the contrast for estimating the main effect A is exactly the same as the contrast used for estimating the BC interaction.
This phenomena is called aliasing and it occurs in all fractional designs
Aliases can be found directly from the columns in the table of + and  signs
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It is clear that from the(se) 4 t.c.’s, we cannot estimate the 7 effects (A, B, AB, C, AC, BC, ABC) present in any 23 design, since each estimate uses (all) 8 t.c’s.
What can be estimated from these 4 t.c.’s?
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4BC = 1 + a  b  ab c  ac + bc + abc
Consider
(4A + 4BC)= 2(a  b  c + abc)
or
2(A + BC)= a  b  c + abc
Overall:
2(A + BC)= a  b  c + abc
2(B + AC)= a + b  c + abc
2(C + AB)= a  b + c + abc
In each case, the 4 t.c.’s NOT run cancel out.
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1, ab, ac, bc,
We would be able to estimate
A  BC
B  AC
C  AB
(generally no better or worse than with + signs)
NOTE: If you “know” (i.e., are willing to assume) that all interactions = 0, then you can say either (1) you get 3 factors for “the price” of 2.
(2) you get 3 factors at “1/2 price.”
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1, ab, c, abc;
We would then estimate
A + B
C + ABC
AC + BC
In each case, we “Lose” 1 effect completely, and get the other 6 in 3 pairs of two effects.
Members of the pair are CONFOUNDED
Members of the pair are ALIASED
two main effects
together usually
less desirable
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In any event, clearly, there are BETTER and WORSE sets of 4 t.c.’s out of a 23.
(Better & worse 231 designs)
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1, ab, ac, bc, ad, bd, cd, abcd
Can estimate: A+BCD
B+ACD
C+ABD
AB+CD
AC+BD
BC+AD
D+ABC
 8 t.c.’s
Lose 1 effect
Estimate other 14 in 7 alias pairs of 2
Note:
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For those who believe, by conviction or via selected empirical evidence, that the world is relatively simple, 3 and higher order interactions (such as ABC, ABCD, etc.) may be announced as zero in advance of the inquiry. In this case, in the 241 above, all main effects are CLEAN. Without any such belief, fractional factorials are of uncertain value. After all, you could get A + BCD = 0, yet A could be large +, BCD large ; or the reverse; or both zero.
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The best way to learn “how” is to work (and discuss) some examples:
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Step 1: In a 2kp, we “lose” 2p1.
Here we lose 1. Choose the effect to lose. Write it as a “Defining relation” or “Defining contrast.”
I = ABDE
Step 2: Find the resulting alias pairs:
*A=BDE AB=DE ABC=CDE
B=ADE AC=4 BCD=ACE
C=ABCDE AD=BE BCE=ACD
D=ABE AE=BD
E=ABD BC=4
CD=4
CE=4
 lose 1
 other 30 in 15 alias pairs of 2
 run 16 t.c.’s
15 estimates
*AxABDE=BDE
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Another option (among many others):
I = ABCDE
A=4 AB=3
B=4 AC=3
C=4 AD=3
D=4 AE=3
E=4 BC=3
BD=3
BE=3
CD=3
CE=3
DE=3
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I II
1 c a ac
ab abc b bc
de cde ade acde
abde abcde bde bcde
ad acd d cd
bd bcd abd abcd
ae ace e ce
be bce abe abce
Same process
as a
Confounding
Scheme
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a
b
ab
c
ac
bc
abc
e
ae
be
abe
ce
ace
bce
abce
Next: Pick which block to run.
(say, block II)
Next: Go out and collect the data.
Next: Analyze it.
a.) find a proper Yates’ order.
i.) pick a letter and for a moment
call it “DEAD.” (assume we pick “d”)
ii.) use the remaining (“live”) letters
to form the STANDARD Yates’ order:
(see right column)
Now append the dead letter as needed to form
the block chosen to be run:
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There’s only one way to do it, i.e. either adding “d” or not adding “d”; one way will work, one won’t.
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252 A, B, C, D, E
Must “lose” 3; other 28
in 7 alias groups of 4
In a 25 , there are 31 effects; with 8 t.c., there are 7 df & 7 estimates available
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must be product of first 2:
I = ABC = BCDE = ADE
A = BC = 5 = DE
B = AC = 3 = 4
C = AB = 3 = 4
D = 4 = 3 = AE
E = 4 = 3 = AD
BD = 3 = CE = 3
BE = 3 = CD = 3
Assume we use this design.
Find alias groups:
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I = ABC = BCDE = ADE
t.c.
yield
(1)
(2)
(3)
Estimate
1
.

.
a (
bd)
2+52
A
.
c (b)
2+34
C
.
ac (d)
AC  +43
B
e (d)
.
4+32
E
D
.
ae (b)
AE 3+4
.
ce (
bd)
CE 3+23
.
ace
ACE 2+32
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t.c. with even # letters in common with evenlettered effect is a + for that effect; t. c. with odd # letters in common with oddlettered effect is a + for that effect; otherwise a  (minus)
abd in ABCDE: 3 in common with 5
ODD with ODD +
abce in ABCDFG: 3 in common with 6
ODD with EVEN 
# letters in effect
Even
Odd
# letters t.c. has in
Common with Effect
Even
Odd
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Interpretation of results often relies on making some assumptions
Ockham’srazor
Confirmation experiments can be important
See the projection of this design into 3 factors
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Every fractional factorial contains full factorials in fewer factors
The “flashlight” analogy
A onehalf fraction will project into a full factorial in any k – 1 of the original factors
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