方法对比
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| 仿真辅助全因子设计× | 中心复合设计× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s (simulation-DOE integration formalized) | 1951 |
| 提出者≠ | Montgomery (DOE foundations); Kleijnen (simulation DOE formalization) | George E. P. Box and K. B. Wilson |
| 类型≠ | Experimental design with computer simulation | Response surface experimental design |
| 开创性文献≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | 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 ↗ |
| 别名 | SA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOE | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| 相关≠ | 4 | 3 |
| 摘要≠ | 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. | 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. |
| ScholarGate数据集 ↗ |
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