Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño Box-Behnken Asistido por Simulación× | Diseño factorial completo asistido por simulación× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1960 (base design); simulation-assisted application developed from the 1990s onward | 1990s–2000s (simulation-DOE integration formalized) |
| Autor original≠ | Box-Behnken (1960) for the base design; simulation integration emerged from computer experiment methodology in the 1980s-2000s | Montgomery (DOE foundations); Kleijnen (simulation DOE formalization) |
| Tipo≠ | Simulation-integrated response surface design | Experimental design with computer simulation |
| 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 ↗ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 |
| Alias | SA-BBD, computer-aided Box-Behnken design, simulation-based BBD, virtual Box-Behnken design | SA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOE |
| Relacionados | 4 | 4 |
| Resumen≠ | Simulation-assisted Box-Behnken design couples the three-level, near-spherical Box-Behnken experimental matrix with computer simulation models — such as finite-element analysis, computational fluid dynamics, or discrete-event simulation — to map how multiple controllable factors jointly affect one or more output responses, while eliminating the need for costly or hazardous physical prototype fabrication at every design point. | Simulation-assisted full factorial design integrates full factorial design of experiments (DOE) with computer simulation models — such as discrete-event simulation, finite element analysis, or Monte Carlo methods — to systematically explore every combination of factor levels and quantify their effects on system responses. It enables comprehensive experimentation in contexts where physical trials would be costly, dangerous, or infeasible. |
| ScholarGateConjunto de datos ↗ |
|
|