A comparison of several design augmentation strategies

Abstract

Industrial experiments often involve many variables, of which only a few are expected to be important. Typically a sequential design approach is used in which a screening phase is followed by a more detailed design on a subset of the variables. Screening designs are usually highly-fractionated factorials or Plackett–Burman designs; the subsequent stages usually involve folding over the Plackett–Burman design, augmenting the fractional factorials, or a completely new less-fractionated factorial using a subset of the original variables. In all of these designs, the alias structure can cause difficulties in detecting the correct model. This paper examines the foldover properties of the Plackett–Burman versus those of three-quarter fractional factorials, comparing and contrasting the efficacy of these two alternative approaches relative to convergence to an a priori known correct model. The results suggest that an initial fractional factorial (that can be subsequently extended to a three-quarter fraction) supports better model identification than the Plackett–Burmann design (with subsequent full foldover). Copyright © 2000 John Wiley & Sons, Ltd.