ABSTRACT
This chapter provides a broad overview of more advanced techniques for optimization called response surface methods (RSM). RSM should be applied only after completing the initial phases of experimentation: Fractional two-level designs that screen the vital few from the trivial many factors and full factorials that study the vital few factors in depth and define the region of interest. The goal of RSM is to generate a map of response, either in the form of contours or as a 3-D rendering. If constructed properly, the central composite design (CCD) provides a solid foundation for generating a response surface map. The CCD contains five levels of each factor: low axial, low factorial, center, high factorial, and high axial. With this many levels, it generates enough information to fit a second-order polynomial called a quadratic. Standard statistical software can do the actual fitting of the model.
