Methoden vergleichen

	Optimierungsgestützte Box-Behnken-Versuchsplanung	Box-Behnken-Design
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1960 (BBD); optimization integration established 1980s–1990s	1960
Urheber	Box & Behnken (design); Derringer & Suich (desirability optimization)	George E. P. Box and Donald W. Behnken
Typ	Experimental design with post-modeling optimization	Response surface design (incomplete three-level factorial)
Wegweisende Quelle	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., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Aliasnamen	BBD with optimization, Box-Behnken design optimization, RSM-BBD optimization, Box-Behnken response optimization	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Verwandt	5	3
Zusammenfassung	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.	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.