6. Proposal to Optimizing Design Using [a, b] Analysis Considering Interaction for Design Matrices Experiment

Hadamard orthogonal tables correspond to interactions in linear graphs. But it only represents part of the interaction. Mixed orthogonal arrays are highly confounding to the main effects of interactions. These experimental design methods capture the main effects, but cannot grasp the interaction. About 62% of the optimal conditions for the mixed system orthogonal array are below the best experimental no. value. This chapter proposes a method for selecting optimal conditions that considers both interactions and main effects. We compared the no. best value condition (a) and the best level condition (b) of the factor effect in the orthogonal array experiment and designed it assuming that the difference level factor was strongly related to the interaction and the common level factor to the main effect. The method is described in detail as [a, b] analysis.