Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño Compuesto Central Asistido por Optimización× | Diseño Box-Behnken× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1951 (CCD); optimization coupling formalized 1970s–1990s | 1960 |
| Autor original≠ | Box & Wilson (CCD, 1951); optimization integration by Myers, Montgomery & colleagues | George E. P. Box and Donald W. Behnken |
| Tipo≠ | Experimental design with mathematical optimization | Response surface design (incomplete three-level factorial) |
| 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., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475. DOI ↗ |
| Alias | CCD with optimization, optimized CCD, RSM-CCD optimization, central composite design with response optimization | BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design |
| Relacionados | 3 | 3 |
| Resumen≠ | Optimization-assisted central composite design (CCD) combines the rotatable, second-order experimental layout of central composite design with mathematical optimization algorithms — typically desirability functions, response surface optimization, or metaheuristics — to find the factor settings that simultaneously maximize, minimize, or hit target values for one or more response variables. It is the most widely applied response-surface optimization workflow in chemical, pharmaceutical, food science, and manufacturing engineering. | The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test. |
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