5.
Process Improvement
5.3.
Choosing an experimental design
5.3.3.
How do you select an experimental design?
5.3.3.6.
Response surface designs
5.3.3.6.4.
|
Blocking a response surface design
|
|
|
How can we block a response surface design?
|
When augmenting a resolution V design to a CCC design by adding
star points, it may be desirable to block the design
|
If an investigator has run either a 2k full factorial
or a 2k-p fractional factorial design of at
least resolution V, augmentation of that design to a central composite
design (either CCC of CCF) is easily accomplished by adding an
additional set (block) of star and centerpoint runs. If the factorial
experiment indicated (via the t test) curvature, this composite
augmentation is the best follow-up option (follow-up options for other
situations will be discussed later).
|
An orthogonal blocked response surface design has advantages
|
An important point to take into account when choosing a response surface
design is the possibility of running the design in blocks. Blocked
designs are better designs if the design allows the estimation of
individual and interaction factor effects independently of the block
effects. This condition is called orthogonal blocking. Blocks are
assumed to have no impact on the nature and shape of the response
surface.
|
CCF designs cannot be orthogonally blocked
|
The CCF design does not allow orthogonal blocking and the Box-Behnken
designs offer blocking only in limited circumstances, whereas the CCC
does permit orthogonal blocking.
|
Axial and factorial blocks
|
In general, when two blocks are required there should be an axial block
and a factorial block. For three blocks, the factorial block is divided
into two blocks and the axial block is not split. The blocking of the
factorial design points should result in orthogonality between blocks
and individual factors and between blocks and the two factor
interactions.
The following Central Composite design in two factors is broken into
two blocks.
|
Table of CCD design with 2 factors and 2 blocks
|
TABLE 3.29: CCD: 2 Factors, 2 Blocks
Pattern
|
Block
|
X1
|
X2
|
Comment
|
|
--
|
1
|
-1
|
-1
|
Full Factorial
|
-+
|
1
|
-1
|
+1
|
Full Factorial
|
+-
|
1
|
+1
|
-1
|
Full Factorial
|
++
|
1
|
+1
|
+1
|
Full Factorial
|
00
|
1
|
0
|
0
|
Center-Full Factorial
|
00
|
1
|
0
|
0
|
Center-Full Factorial
|
00
|
1
|
0
|
0
|
Center-Full Factorial
|
-0
|
2
|
-1.414214
|
0
|
Axial
|
+0
|
2
|
+1.414214
|
0
|
Axial
|
0-
|
2
|
0
|
-1.414214
|
Axial
|
0+
|
2
|
0
|
+1.414214
|
Axial
|
00
|
2
|
0
|
0
|
Center-Axial
|
00
|
2
|
0
|
0
|
Center-Axial
|
00
|
2
|
0
|
0
|
Center-Axial
|
Note that the first block includes the full factorial points and three
centerpoint replicates. The second block includes the axial points and
another three centerpoint replicates. Naturally these two blocks
should be run as two separate random sequences.
|
Table of CCD design with 3 factors and 3 blocks
|
The following three examples show blocking structure for various designs.
TABLE 3.30: CCD: 3 Factors 3 Blocks, Sorted by Block
Pattern
|
Block
|
X1
|
X2
|
X3
|
Comment
|
|
---
|
1
|
-1
|
-1
|
-1
|
Full Factorial
|
-++
|
1
|
-1
|
+1
|
+1
|
Full Factorial
|
+-+
|
1
|
+1
|
-1
|
+1
|
Full Factorial
|
++-
|
1
|
+1
|
+1
|
-1
|
Full Factorial
|
000
|
1
|
0
|
0
|
0
|
Center-Full Factorial
|
000
|
1
|
0
|
0
|
0
|
Center-Full Factorial
|
--+
|
2
|
-1
|
-1
|
+1
|
Full Factorial
|
-+-
|
2
|
-1
|
+1
|
-1
|
Full Factorial
|
+--
|
2
|
+1
|
-1
|
-1
|
Full Factorial
|
+++
|
2
|
+1
|
+1
|
+1
|
Full Factorial
|
000
|
2
|
0
|
0
|
0
|
Center-Full Factorial
|
000
|
2
|
0
|
0
|
0
|
Center-Full Factorial
|
-00
|
3
|
-1.63299
|
0
|
0
|
Axial
|
+00
|
3
|
+1.63299
|
0
|
0
|
Axial
|
0-0
|
3
|
0
|
-1.63299
|
0
|
Axial
|
0+0
|
3
|
0
|
+1.63299
|
0
|
Axial
|
00-
|
3
|
0
|
0
|
-1.63299
|
Axial
|
00+
|
3
|
0
|
0
|
+1.63299
|
Axial
|
000
|
3
|
0
|
0
|
0
|
Axial
|
000
|
3
|
0
|
0
|
0
|
Axial
|
|
Table of CCD design with 4 factors and 3 blocks
|
TABLE 3.31 CCD: 4 Factors, 3 Blocks
Pattern
|
Block
|
X1
|
X2
|
X3
|
X4
|
Comment
|
|
---+
|
1
|
-1
|
-1
|
-1
|
+1
|
Full Factorial
|
--+-
|
1
|
-1
|
-1
|
+1
|
-1
|
Full Factorial
|
-+--
|
1
|
-1
|
+1
|
-1
|
-1
|
Full Factorial
|
-+++
|
1
|
-1
|
+1
|
+1
|
+1
|
Full Factorial
|
+---
|
1
|
+1
|
-1
|
-1
|
-1
|
Full Factorial
|
+-++
|
1
|
+1
|
-1
|
+1
|
+1
|
Full Factorial
|
++-+
|
1
|
+1
|
+1
|
-1
|
+1
|
Full Factorial
|
+++-
|
1
|
+1
|
+1
|
+1
|
-1
|
Full Factorial
|
0000
|
1
|
0
|
0
|
0
|
0
|
Center-Full Factorial
|
0000
|
1
|
0
|
0
|
0
|
0
|
Center-Full Factorial
|
----
|
2
|
-1
|
-1
|
-1
|
-1
|
Full Factorial
|
--++
|
2
|
-1
|
-1
|
+1
|
+1
|
Full Factorial
|
-+-+
|
2
|
-1
|
+1
|
-1
|
+1
|
Full Factorial
|
-++-
|
2
|
-1
|
+1
|
+1
|
-1
|
Full Factorial
|
+--+
|
2
|
+1
|
-1
|
-1
|
+1
|
Full Factorial
|
+-+-
|
2
|
+1
|
-1
|
+1
|
-1
|
Full Factorial
|
++--
|
2
|
+1
|
+1
|
-1
|
-1
|
Full Factorial
|
++++
|
2
|
+1
|
+1
|
+1
|
+1
|
Full Factorial
|
0000
|
2
|
0
|
0
|
0
|
0
|
Center-Full Factorial
|
0000
|
2
|
0
|
0
|
0
|
0
|
Center-Full Factorial
|
-000
|
3
|
-2
|
0
|
0
|
0
|
Axial
|
+000
|
3
|
+2
|
0
|
0
|
0
|
Axial
|
0-00
|
3
|
0
|
-2
|
0
|
0
|
Axial
|
0+00
|
3
|
0
|
+2
|
0
|
0
|
Axial
|
00-0
|
3
|
0
|
0
|
-2
|
0
|
Axial
|
00+0
|
3
|
0
|
0
|
+2
|
0
|
Axial
|
000-
|
3
|
0
|
0
|
0
|
-2
|
Axial
|
000+
|
3
|
0
|
0
|
0
|
+2
|
Axial
|
0000
|
3
|
0
|
0
|
0
|
0
|
Center-Axial
|
0000
|
3
|
0
|
0
|
0
|
0
|
Center-Axial
|
|