The Use of Plackett–Burman Designs to Construct Split-Plot Designs

Abstract

When some factors are hard to change and others are relatively easier, split-plot experiments are often an economic alternative to fully randomized designs. Split-plot experiments, with their structure of subplot arrays imbedded within whole-plot arrays, have a tendency to become large, particularly in screening situations when many factors are considered. To alleviate this problem, we explore, for the case of two-level designs, various ways to use orthogonal arrays of the Plackett–Burman type to reduce the number of individual tests. General construction principles are outlined, and the resulting alias structure is derived and discussed.

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