Journal of Quality Technology vol. 43 issue 1 - January 2011
Abstract: [This abstract is based on the authors' abstract.] Screening designs help assess the relative impact of a large number of factors. Experimenters often prefer quantitative factors to have three levels rather than two, but common screening designs use only two factors. This article proposes a new class of three-level designs that is unbiased by second order effects, require only one more than twice as many runs as factors and avoid confounding any pair of second order effects. The new class of designs also allows for efficient estimation of the full quadratic model for any three factors if six or more factors exist, potentially rendering followup experiments unnecessary. The article provides an algorithm for use in design construction.
Keywords: Algorithm; Alias; Confounding; Design of experiments (DOE); Factor analysis; Modeling; Response surface methodology (RSM); Robust design; Screening
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