Response surface design methodology is often used to refine models after
you have determined important factors using screening designs or factorial
designs; especially if you suspect curvature in the response surface.
For example, an engineer wants to analyze the injection-molding process for
a plastic part. First, the engineer performs a fractional factorial design,
identifies the important factors (temperature, pressure, cooling rate), and
determines that curvature is present in the data. Then, the engineer creates a
central composite design to analyze the curvature and find the best factor
settings. To see an example, go to
Example of Create Response Surface Design
There are two main types of response surface designs.
- Central Composite designs
- Central Composite designs can fit a full quadratic model. They are
often used when the design plan calls for sequential experimentation because
these designs can include information from a correctly planned factorial
- Box-Behnken designs
- Box-Behnken designs usually have fewer design points than central
composite designs; therefore, they are less expensive to run with the same
number of factors. They can efficiently estimate the first- and second-order
coefficients; however, they cannot include runs from a factorial experiment.
Box-Behnken designs always have 3 levels per factor, unlike central composite
designs, which can have up to 5. Also, unlike central composite designs,
Box-Behnken designs never include runs where all factors are at their extreme
setting, such as all the low settings.
For more information on available designs, go to
What are response surface designs, central
composite designs, and Box-Behnken designs?.