Factorial planning and response surface for the definition of experimental parameters in scientific research, A review

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Author: 
Claudiany S. Leite Lima, Danielle C. Barros, Davi T. Reis, Denis S. Passos, Naiane G. Silva, Pedro G. B. Bonfim, Vanessa M. Mattje, Gessiel Newton Sheidt and Augustus Caeser Franke Portella
Subject Area: 
Physical Sciences and Engineering
Abstract: 

In order to obtain the optimization of a given experiment, we need to carry out a triage, using either full or fractional factorial planning. These are statistical procedures that seek to minimize the work required. This eliminates the variables called factors, which are not significant in the experiment. Factorial planning basically consists of carrying out a survey of the factors of the proposed experiment and evaluating the effects they exert on each other and on the final result. The Response Surface Methodology (RSM) consists of a collection of mathematical and statistical techniques based on the fit of a polynomial equation to the experimental data, which should describe the behavior of a dataset in order to make statistical predictions. The objective of the present work is to synthesize the theoretical and practical knowledge of the methodology of Factorial Planning and RSM as statistical tools for evaluation and optimization of parameters involved in an experimental scientific research project.

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