The method was introduced by George E. The main idea of RSM is to use a sequence of designed experiments to obtain response surface methodology book pdf optimal response.
Box and Wilson suggest using a second-degree polynomial model to do this. They acknowledge that this model is only an approximation, but they use it because such a model is easy to estimate and apply, even when little is known about the process.
Statistical approaches such as RSM can be employed to maximize the production of a special substance by optimization of operational factors. In contrast to conventional methods, the interaction among process variables can be determined by statistical techniques.
An easy way to estimate a first-degree polynomial model is to use a factorial experiment or a fractional factorial design. Once it is suspected that only significant explanatory variables are left, then a more complicated design, such as a central composite design can be implemented to estimate a second-degree polynomial model, which is still only an approximation at best. Also orthogonality provides minimum variance estimates of the model coefficient so that they are uncorrelated.
ROTATABILITY: The property of rotating points of the design about the center of the factor space. The moments of the distribution of the design points are constant.