Comparar métodos

	Diseño Compuesto Central Robusto	Metodología de Superficie de Respuesta (RSM)
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Hypothesis test
Año de origen	1951 (CCD); robust integration from 1980s–1990s	1951
Autor original	George E. P. Box & K. B. Wilson (CCD foundation); robust extension via Taguchi and Myers–Montgomery tradition	George E. P. Box & K. B. Wilson
Tipo	Experimental design with robust optimization	Second-order polynomial response surface model
Fuente seminal	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2009). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (3rd ed.). Wiley. ISBN: 978-0470174463	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	Robust CCD, CCD with robust optimization, robust RSM with CCD, robust response surface CCD	RSM, Central Composite Design, Box-Behnken Design, CCD
Relacionados	4	7
Resumen	Robust Central Composite Design (Robust CCD) combines the efficient quadratic fitting capability of the central composite design with robust optimization principles to find factor settings that simultaneously achieve a target mean response and minimize the effect of uncontrollable noise factors on response variability. It is widely applied in manufacturing, chemical engineering, and product development when both performance and consistency under real-world variation are critical.	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.