Determination of optimum experimental conditions using dispersion main effects and interactions of factors in replicated factorial experiments

Abstract

Dispersion main effects and two-factor interactions are first defined and then estimated in replicated factorial experiments. A method based on Union-Intersection rules, using dispersion main effects and two factor interactions is proposed for finding the level combinations of control factors so that the response variability due to noise is minimum. Illustrative examples are also given.