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5.
Process Improvement
5.3. Choosing an experimental design 5.3.3. How do you select an experimental design?
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| Full factorial
experiments can require many runs
A carefully chosen fraction of the runs may be all that is necessary Later sections will show how to choose the "right" fraction for 2-level designs - these are both balanced and orthogonal |
The ASQC (1983) Glossary & Tables for Statistical Quality
Control defines fractional factorial design in the following way: “A
factorial experiment in which only an adequately chosen fraction of the
treatment combinations required for the complete factorial experiment is
selected to be run.”
Even if the number of factors, k, in a design is small, the 2k specified for a full factorial can quickly become very large. For example, 26 = 64 is a two-level, full factorial design with six factors. To this design we need to add a good number of center point runs and we can quickly run up a very large resource requirement for runs with only a modest number of factors. The solution to this problem is to run only a fraction of the runs specified by the full factorial design. Which runs to do and which to leave out is the subject of interest here. In general, we pick a fraction such as ½, ¼, etc. of the runs called for by the full factorial. We use various strategies that ensure an appropriate choice of runs. The following sections will show you how to choose an appropriate fraction of a full factorial design to suit your purpose at hand. Properly chosen fractional factorial designs for 2-level experiments have the desirable properties of being both balanced and orthogonal. Note: We will be emphasizing fractions of two-level designed experiments only. This is because two-level fractional designs are, in engineering at least, by far the most popular fractional design. Fractional factorials where some factors have three levels will be covered briefly in Section 5.3.3.10. |
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