方法对比
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| 基于风险的实验设计× | 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≠ | 2000s–2010s (formalized in pharmaceutical and process engineering contexts) | 1951 |
| 提出者≠ | Emerged from ICH Q8/Q9/Q10 pharmaceutical guidelines; formalized in engineering by integration of FMEA/FTA with classical DoE | George E. P. Box & K. B. Wilson |
| 类型≠ | Experimental design method with risk-based factor prioritization | Second-order polynomial response surface model |
| 开创性文献≠ | Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916018 | 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≠ | Risk-based DoE, risk-informed experimental design, risk-prioritized DoE, RB-DoE | RSM, Central Composite Design, Box-Behnken Design, CCD |
| 相关≠ | 4 | 7 |
| 摘要≠ | Risk-based design of experiments (RB-DoE) integrates formal risk assessment — typically using tools such as FMEA or fault tree analysis — with classical experimental design to prioritize which process or product factors are most critical to investigate. Rather than treating all candidate factors equally, this approach ranks factors by their risk priority number or likelihood of affecting quality, safety, or reliability, then allocates experimental runs preferentially to high-risk factors. It is widely used in pharmaceutical development, chemical process engineering, and manufacturing quality management. | 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. |
| ScholarGate数据集 ↗ |
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