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Full-factorial designs consider all possible combinations of factor settings involved. However, as the number of factors increases, the number of experiments increases dramatically. In these cases, fractional factorial designs are used. The reduced number of runs associated with fractional factorials results in potential aliases among main effects and their interactions. To resolve this situation, fractional factorial designs are often augmented. This article presents an alternative way of augmenting resolution IV fractions using small sets of runs to decouple specific interactions in targeted alias chains. The new method is compared to its competitors, the complete foldover and the semi-fold.
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Misra et al. (2013) studied this question.
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