方法对比
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| 分数析因实验× | 响应面方法 (RSM)× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族≠ | Process / pipeline | Hypothesis test |
| 起源年份≠ | 1945 (Finney); broader development 1950s–1970s by Box, Hunter | 1951 |
| 提出者≠ | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work | George E. P. Box & K. B. Wilson |
| 类型≠ | Quantitative experimental design | Second-order polynomial response surface model |
| 开创性文献≠ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 | 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. link ↗ |
| 别名≠ | fractional factorial design, FFD, 2^(k-p) design, fractional replication | RSM, Central Composite Design, Box-Behnken Design, CCD |
| 相关≠ | 4 | 7 |
| 摘要≠ | A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments. | 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. |
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