Dispersion Effects From 7 Unreplicated Designs in the 2 k — p Series

Abstract

Quality improvement requires reduction of undesired variation. Design of experiments haa become a useful tool for discovering such minimum variance conditions, but most existing techniques require a large experimental effort involving replicated experiments. In this article we develop a method for significance testing of dispersion effects from unreplicated two-level fractional factorial experiments using principles close to those for identifying location effects. The method provides an F-distributed test statistic and appears to be useful for identification of dispersion effects as early as the screening stage when fractionated unreplicated experiments are frequently employed.

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