Why use response surface models

The important technique of response surface modelling for the study of how response variables are related to variations in the experimental conditions was introduced by George E. P. Box and coworkers early in the fifties. [1] The technique has been extensively used in many areas of experimental work. It is especially well suited to the study of synthetic chemical procedures, and this was actually one of the first areas to which the method was applied.[2] 

In the preceding chapters it was discussed how a near-optimum experimental domain can be found by the method of steepest ascent or by a simplex search. However, these methods cannot be used to efficiently locate the optimum conditions. For this, response surface modelling is a far more efficient technique. 

The principles behind response surface modelling are simple. If the experimental domain is not too large, an unknown theoretical response function, f 

From the model it is then possible to analyze the roles played by the experimental variables. The model will be a map of the explored domain. 

The technique to establish the response surface models is also simple  

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