is the difference between Taguchi orthogonal array
designs and Taguchi robust designs in DOE++?
Both Taguchi orthogonal array designs and Taguchi
robust designs are based on the work of Dr. Genichi
Taguchi. The design types serve different purposes,
however, and are created in different ways.
Taguchi orthogonal arrays are a type of general
fractional factorial design. These highly fractional
orthogonal designs, based on a design matrix proposed by
Dr. Genichi Taguchi, allow you to consider a selected
subset of combinations of multiple factors at multiple
levels. Orthogonal arrays are balanced to ensure that
all levels of all factors are considered equally. For
this reason, the factors can be evaluated independently
of each other despite the fractionality of the design.
To create a Taguchi orthogonal array (OA) design in
software , select Factorial
Design in Step 1 of the
Design Wizard and then select Taguchi OA Factorial
Design in Step 2.
Taguchi OA designs deal exclusively with "control
factors," or factors of interest. If you need to deal
with "noise factors," or factors beyond the control of
the operator, you should use a Taguchi robust design.
The purpose of Taguchi robust designs is to minimize
the variability of the response in spite of noise
factors. This is done by combining an inner array of
control factors with an outer array of noise factors.
All control factor settings combinations specified in
the inner array are tested at each noise factor settings
combination specified in the outer array. In DOE++,
the inner array can use a Taguchi OA, two level full
factorial, two level fractional factorial,
Plackett-Burman or general full factorial design. The
outer array can use a two level full factorial, two
level fractional factorial, Plackett-Burman or general
full factorial design.
To create a Taguchi robust design in DOE++, select Taguchi
Robust Design in Step 1 of the Design Wizard.
Once you have created the Taguchi robust design and
entered the data, you can specify the equation to be
used in calculating the signal-to-noise ratio. Your
selection for this option is determined by the purpose
of your analysis:
- Nominal (or "nominal-the-best") should be used
if you have a specific target value for the
- Larger (or "larger-the-better") should be used
if you want to maximize the value of the response.
- Smaller (or "smaller-the-better") should be used
if you want to minimize the value of the response.
can I find out when ReliaSoft has issued a free Service Release?
ReliaSoft uses minor version "service releases" to
resolve any critical issues with the software. These
updates are free to registered users. We recommend that
you check occasionally to ensure that you always have
the latest fixes and enhancements. There are two easy
ways to stay informed about the latest updates:
- Check the ReliaSoft.com Web site. New service releases are
announced on the site home page and the latest build
number (e.g. 7.5.9) is identified in the upper right
corner of each product home page. If the build date
displayed in the About window for the software on your
computer does not match the latest build, click the
Update link on the Web page to download the latest
Service Release installation.
- Sign up for a
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