I need to build up knowledge about Design of Experiments and have a fundamental question about the real goal of DoE. Most classical texts start with discussing in considerable detail full factorial design plans where each factor only has two levels. The underlying statistical model is (multi-)linear. However I wonder whether these models are really that important in practice. I.e., I would rather expect that most factors are continuous rather than dichotomic, like e.g. temperature in the design of a reactor. Then, a linear model would not allow to find an optimum but at best the direction in which to look for an optimum.