Abstract
ABSTRACT Dynamic processes undergo a transition time when changing experimental factors and therefore an experimenter is often interested in estimating effect dynamics alongside effect sizes. This article illustrates an eight-step analysis procedure for model identification of a multiple-input transfer function–noise model for the response from a two-level factorial experiment in a blast furnace process. Because real data often are affected by disturbances and missing observations, our proposed procedure deals with these problems and results in a transfer function–noise model that captures system dynamics and provides effect estimates from the experiment.
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