Supersaturated designs: set-ups, data interpretation, and analytical applications
Abstract
For screening purposes, two-level screening designs, such as fractional factorial (FF) and Plackett–Burman (PB) designs, are usually applied. These designs enable examination of, at most, N−1 factors in N experiments. However, when many factors need to be examined, the number of experiments still becomes unfeasibly large. Occasionally, in order to reduce time and costs, a given number of factors can be examined in fewer experiments than with the above screening designs, by using supersaturated designs. These designs examine more than N SS−1 factors in N SS experiments. In this review, different set-ups to construct supersaturated designs are explained and discussed, followed by several possible data interpretations of supersaturated design results. Finally, some analytical applications of supersaturated designs are given.
Keywords
Supersaturated designs Set-up Data interpretation Analytical applicationReferences
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