However it is very useful to go in for a fractional factorial
design when the number of factors is large and when it is
expected some factors or interactions between some
factors to be unimportant.
The fractional factorial experiment design is useful when
main effects dominate with interaction effects being of
lower order.
DOE
–
Fractional Factorial Designs

33
Taguchi Method

DOE - Taguchi Method
34
Dr. Taguchi of Nippon Telephones and Telegraph
Company, Japan has developed a method based on "
ORTHOGONAL ARRAY " experiments.
This gives much reduced " variance " for the experiment
with " optimum settings " of control parameters.
"Orthogonal Arrays" (OA) provide a set of well balanced
(minimum) experiments serve as objective functions for
optimization.

Taguchi Method : When to Select a
‘
larger
’
OA
to perform
“
Factorial Experiments
”
35
We always
‘
think
’
about
‘
reducing
’
the number of
experiments (to minimize the
‘
resources
’ –
equipment,
materials, manpower and time
)
However, doing ALL / Factorial experiments is a good idea
if
Conducting experiments is
‘
cheap/quick
’
but
measurements are
‘
expensive/take too long
’
The experimental facility will
NOT be available later to
conduct the
‘
verification
’
experiment
We do
NOT wish to conduct
separate experiments for
studying interactions between
Factors

Taguchi Method Design of Experiments
36
The general steps involved in the Taguchi Method are as
follows:
1.
Define the process objective, or more specifically, a target value for a
performance measure of the process.
2.
Determine the design parameters affecting the process.
3.
The number of levels that the parameters should be varied at must be
specified.
4.
Create orthogonal arrays for the parameter design indicating the number
of and conditions for each experiment.
5.
The selection of orthogonal arrays is based on the number of parameters
and the levels of variation for each parameter, and will be expounded
below.
6.
Conduct the experiments indicated in the completed array to collect data
on the effect on the performance measure.
7.
Complete data analysis to determine the effect of the different
parameters on the performance measure.

Determining Parameter Design Orthogonal Array
37
The effect of many different factors on the performance characteristic in a
condensed set of experiments can be examined by using the orthogonal array
experimental design proposed by Taguchi.
The main factors affecting a process that can be controlled (control Factors)
should be determined.
The levels at which these parameters should be varied must be determined.
Determining what levels of a variable to test requires an in-depth understanding of
the process, including the minimum, maximum, and current value of the
parameter.

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- Spring '19
- Magdy Khalaf
- Fractional factorial designs, Factorial Designs