Porównaj metody

	Optymalizacja wspomagana planowaniem Boxa-Behnkena	Metodologia Powierzchni Odpowiedzi (RSM)
Dziedzina	Planowanie eksperymentów	Planowanie eksperymentów
Rodzina	Process / pipeline	Hypothesis test
Rok powstania	1960 (BBD); optimization integration established 1980s–1990s	1951
Twórca	Box & Behnken (design); Derringer & Suich (desirability optimization)	George E. P. Box & K. B. Wilson
Typ	Experimental design with post-modeling optimization	Second-order polynomial response surface model
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.	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.
Inne nazwy	BBD with optimization, Box-Behnken design optimization, RSM-BBD optimization, Box-Behnken response optimization	RSM, Central Composite Design, Box-Behnken Design, CCD
Pokrewne	5	7
Podsumowanie	Optimization-assisted Box-Behnken design (BBD) combines the Box-Behnken three-level experimental design with a formal optimization step to locate factor settings that maximize, minimize, or hit a target for one or more responses. BBD fits a second-order response surface model using fewer runs than a full factorial, and the optimization stage — typically via desirability functions or numerical search — then exploits that fitted model to identify the true optimum within the experimental region.	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.