Response Surface Methodology

RESPONSE SURFACE METHODOLOGY
The RSM, response surface methodology, is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response ofinterest is influenced by several variables. The objective of this method is to optimize this response (Bradley, 2007).
The most extensive application of RSM is in the industrial world, particularlyin situations where several input variables potentially influence some performance measure or quality characteristic of the product or process. This performance measure or quality characteristic iscalled the response. It is typically measured on a continuous scale, although attribute responses, ranks, and sensory responses are not unusual (Myers, Montgomery and Anderson-Cook, 2009).
Someareas where the RSM is used are in the design, development and formulation of new products, as well as in the improvement of existing product designs.
An example of the application of this methodologyis the following. The growth of a plant is affected by a certain amount of water (variable 1) and sunshine (variable 2). The plant will grow under any combination of treatment of the variable 1 and 2.Therefore, water and sunshine can vary continuously. When the treatments are from a continuous range of values, the response surface methodology will be useful for developing, improving and optimizingthe response variable (Bradley, 2007).
In the next image there is an example of some graphs that are obtained using the response surface methodology. These are useful for detecting, in a visualway, the areas or optimum values of the independent variables where the response variable (dependent variable) is at the optimum level, whether maximized, minimized or other option.

Image 1. Usualresponse surface methodology plots (Myers, Montgomery and Anderson-Cook, 2009).

BIBLIOGRAPHY
N. Bradley. 2007. The response surface methodology. Indiana (USA). Indiana University of South Bend....