A structural method of setting up large numbers of experiments where the components being tested are set at different ratios or mixtures in relation to each other. The experiments are designed to control or manage variability in multiple directions. This approach also helps identify and control extraneous variables that could otherwise lead to accidental misinterpretation of the dataset.