Comparar métodos

	Experimento Factorial Fraccionado	Metodología de Superficie de Respuesta (RSM)
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Hypothesis test
Año de origen	1945 (Finney); broader development 1950s–1970s by Box, Hunter	1951
Autor original	D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work	George E. P. Box & K. B. Wilson
Tipo	Quantitative experimental design	Second-order polynomial response surface model
Fuente seminal	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130	Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45.
Alias	fractional factorial design, FFD, 2^(k-p) design, fractional replication	RSM, Central Composite Design, Box-Behnken Design, CCD
Relacionados	4	7
Resumen	A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments.	Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics.