%0 Journal Article
	%A Jesús Everardo Olguín Tiznado and  Rafael García Martínez and  Claudia Camargo Wilson and  Juan Andrés López Barreras and 
Everardo Inzunza González and  Javier Ordorica Villalvazo
	%D 2012
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 66, 2012
	%T Effect of Size of the Step in the Response Surface Methodology using Nonlinear Test Functions
	%U https://publications.waset.org/pdf/3567
	%V 66
	%X The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.
	%P 1091 - 1096