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| Projekt Boxa-Behnkena oparty na analizie ryzyka× | Box-Behnken Design× | |
|---|---|---|
| Dziedzina | Planowanie eksperymentów | Planowanie eksperymentów |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 2005–2009 (QbD-era integration of risk assessment with BBD) | 1960 |
| Twórca≠ | Box & Behnken (BBD, 1960); risk integration formalized under ICH Q8/Q9 pharmaceutical QbD frameworks (~2005–2009) | George E. P. Box and Donald W. Behnken |
| Typ≠ | Response surface experimental design with risk prioritization | Response surface design (incomplete three-level factorial) |
| Źródło pierwotne | 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., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475. DOI ↗ |
| Inne nazwy | Risk-based BBD, Risk-prioritized Box-Behnken, QbD Box-Behnken design, Risk-informed RSM | BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design |
| Pokrewne≠ | 4 | 3 |
| Podsumowanie≠ | Risk-based Box-Behnken Design combines the classical three-level Box-Behnken response surface design with a formal risk assessment step — typically a risk ranking tool such as FMEA or Ishikawa analysis — to prioritize which process or formulation factors deserve experimental investigation. Widely adopted in pharmaceutical Quality by Design (QbD) and engineering process optimization, the approach ensures that experimental resources are directed toward the factor combinations most likely to affect product quality or process performance, reducing unnecessary runs while preserving predictive power. | The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test. |
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