Metodología de Superficie de Respuesta
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2017-06
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Jaén: Universidad de Jaén
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[ES] El objetivo del presente trabajo es desarrollar la Metodología de Superficie de Respuesta, así como todas las técnicas que intervienen en el proceso. Para ello se han ilustrado dos ejemplos en los cuales se utiliza dicha metodología con el fin último de conseguir la optimización de una variable respuesta, es decir, la variable que recibe influencia de diversos factores. Para conseguir dicha optimización, será necesario en primer lugar determinar las mejores condiciones de los factores que intervienen en los procesos mediante diseños 2^k. Posteriormente, se podrán aplicar las técnicas para la optimización de la respuesta tales como: el diseño central compuesto o Box-Behnken. Esta elección dependerá de cada caso.
[EN]The objective of the present work is to develop the Response Surface Methodology, as well as all the techniques that intervene in the process. In order to do this, two examples have been illustrated in which the methodology is used with the ultimate aim of achieving the optimization of a response variable, that is, the variable that is influenced by several factors. In order to achieve this optimization, it will be necessary firstly to determine the best conditions of the factors involved in the process by means of 2^k designs. Subsequently, the techniques for the optimization of the response can be applied such as: the composite central design or Box-Behnken design. This choice will depend on the case in which the study is found.
[EN]The objective of the present work is to develop the Response Surface Methodology, as well as all the techniques that intervene in the process. In order to do this, two examples have been illustrated in which the methodology is used with the ultimate aim of achieving the optimization of a response variable, that is, the variable that is influenced by several factors. In order to achieve this optimization, it will be necessary firstly to determine the best conditions of the factors involved in the process by means of 2^k designs. Subsequently, the techniques for the optimization of the response can be applied such as: the composite central design or Box-Behnken design. This choice will depend on the case in which the study is found.