Comparar métodos
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| Diseño Robusto Box-Behnken× | Diseño Compuesto Central× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1960 (BBD); robust integration practice emerged 1990s–2000s | 1951 |
| Autor original≠ | Box & Behnken (BBD foundation); robust integration drawing on Taguchi (1986) and Myers et al. | George E. P. Box and K. B. Wilson |
| Tipo≠ | Experimental design with robustness optimization | Response surface experimental design |
| Fuente seminal≠ | 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 ↗ | 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. DOI ↗ |
| Alias | Robust BBD, BBD robust parameter design, robust response surface BBD, noise-robust Box-Behnken | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| Relacionados≠ | 4 | 3 |
| Resumen≠ | Robust Box-Behnken design combines the efficiency of the Box-Behnken design (BBD) — a three-level response surface design requiring no corner runs — with robust parameter design principles to identify factor settings that optimize the mean response while simultaneously minimizing sensitivity to uncontrollable noise factors. It is widely applied in manufacturing, chemical engineering, and product development when both performance and consistency under real-world variation matter. | Central Composite Design (CCD) is a second-order response surface design that allows researchers to efficiently fit a full quadratic model relating multiple continuous input factors to one or more response variables. Introduced by Box and Wilson in 1951, it combines a factorial (or fractional factorial) core, axial (star) points, and center-point replicates into a single unified design, making it the most widely used design for process optimization in engineering, chemistry, and manufacturing. |
| ScholarGateConjunto de datos ↗ |
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