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| Bayesiansk Box-Behnken-design× | Box-Behnken-design – Responsyte-metodik med tre nivåer× | |
|---|---|---|
| Ämnesområde | Försöksplanering | Försöksplanering |
| Familj | Process / pipeline | Process / pipeline |
| Ursprungsår≠ | 1960 (BBD); Bayesian integration ~1990s–2000s | 1960 |
| Upphovsperson≠ | Box & Behnken (classical BBD, 1960); Bayesian extension developed by multiple authors in response surface literature | George E. P. Box and Donald W. Behnken |
| Typ≠ | Bayesian response surface experimental design | Response surface design (incomplete three-level factorial) |
| Ursprungskälla | 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 ↗ |
| Alias | Bayesian BBD, Bayesian RSM Box-Behnken, Bayesian three-level design, BBD with Bayesian optimization | BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design |
| Närliggande≠ | 5 | 3 |
| Sammanfattning≠ | Bayesian Box-Behnken Design combines the classical Box-Behnken three-level design structure with Bayesian statistical inference to fit and optimize response surface models. It uses mid-edge and center points to efficiently estimate a second-order polynomial response surface while incorporating prior knowledge about model parameters and propagating uncertainty through to predictions and optimal factor settings. The approach is widely applied in engineering process optimization and formulation studies. | 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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