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:: Home ::Six Sigma ::SIX SIGMA GLOSSARY: Inner and Outer Arrays :: CURRENT STUDENTS LOGIN

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Inner and Outer Arrays
 

Taguchi type experimental designs distinguish between 'noise' factors and 'control' factors. Control factors are put in the 'inner array' and noise factors in the outer array. An example is shown below. The experiment is to find the best values for the three design features in a relief valve: Hole Size, Spring Length and Ball Size. The noise factors are the Oil Temperature and Water Vapor Pressure.

Outer Array
D Oil Temperature
1
2
1
2
 
E Water Vapor Pressure
1
1
2
2
 
 
Inner Array
         
 
A (hole)
B (spring)
AB
C (ball)
AC
BC
-
         
Treatment
1
2
3
4
5
6
7
       
S/N Min
1
1
1
1
1
1
1
1
44.9
51.9
52.6
59.9
-34.42
2
1
1
1
2
2
2
2
102.0
113.5
125.0
99.0
-40.86
3
1
2
2
1
1
2
2
47.3
51.3
54.1
61.1
-34.60
4
1
2
2
2
2
1
1
111.0
103.0
104.0
127.5
-40.97
5
2
1
2
1
2
1
2
157.8
157.2
154.3
165.2
-44.01
6
2
1
2
2
1
2
1
188.5
194.0
211.5
197.5
-45.94
7
2
2
1
1
2
2
1
148.6
159.5
198.0
176.7
-44.70
8
2
2
1
2
1
1
2
220.0
198.5
217.5
220.0
-46.62
S/N avg @ 2
-45.31
-41.72
-41.38
-43.59
-42.63
-41.52
-41.52
         
S/N avg @ 1
-37.71
-41.31
-41.65
-39.43
-40.39
-41.50
-41.51
         
Δ S/N
-7.60
-0.41
0.27
-4.16
-2.24
-0.02
-0.01
         

The analysis gives the control factor settings that maximize the Signal to Noise Ratio and hence minimize the loss.

 

The Design of Experiments is covered in the MiC Quality basic Design of Experiments course and Advanced Design of Experiments course.

Try out our courses by taking the first module of the Primer in Statistics free of charge.

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