Nonregular Designs With Desirable Projection Properties

In many industrial applications, the experimenter is interested in estimating some of the main effects and two-factor interactions. In this article we rank two-level orthogonal designs based on the number of estimable models containing a subset of main effects and their associated two-factor interactions. By ranking designs in this way, the experimenter can directly assess the usefulness of the experimental plan for the purpose in mind. We apply the new ranking criterion to the class of all non isomorphic two-level orthogonal designs with 16 and 20 runs and introduce a computationally efficient algorithm, based on two theoretical results, which will aid in finding designs with larger run sizes. Catalogs of useful designs with 16, 20, 24, and 28 runs are presented.