Hello,

I have some new questions about factor interactions that I would like to expose
to you.
In my problem I have identified 4 factors (A,B,C and D) with three levels each.
So I adopted a L9 array.
The first level of factor D depends on factor A and C.

According to DOE using Taguchi approach from Ranjit Roy, the trial conditions
are unaffected by interactions and I understand that it means I may start the
experimental research (without previously knowing if there are or not
interaction factors).

I believe that if there are interactions between the factors that I want to
study, its effect is really low.

However I do not know if am I doing it right for factor D since its first level
depends on A and C…

Can I proceed with the 9 tests without knowing those answers? These tests are
expensive and I also do not have enough time to spend.

Is it possible to use QT4 to identify interaction factors and its significant
(or not) after all tests were made using L9 array?

Another question:
both the process of designing the experiment and the statistical analyses of the
results are considered in the Taguchi approach, which is based on the use of
orthogonal array, associated with the analysis of variance (ANOVA), and the
significance test with F statistic.
Why is it used the F statistic and not other type of significance test?

I would appreciate if you could answer to my questions.

Thank you very much.

Ana B.