Methoden vergleichen

	Optimierungsgestützte Response Surface Methodology	Box-Behnken-Design
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1951 (RSM); 1980 (desirability-function optimization formalized)	1960
Urheber	Derringer & Suich (desirability function); Box & Wilson (RSM foundation)	George E. P. Box and Donald W. Behnken
Typ	Hybrid experimental-optimization framework	Response surface design (incomplete three-level factorial)
Wegweisende Quelle	Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219.	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	OA-RSM, RSM with optimization, desirability-based RSM, multi-response RSM optimization	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Verwandt	5	3
Zusammenfassung	Optimization-assisted RSM couples a second-order response surface model with a mathematical optimization routine — most commonly Derringer and Suich's desirability function, but also genetic algorithms or gradient-based solvers — to locate the factor settings that simultaneously satisfy multiple quality or performance objectives. The result is a data-driven recommendation for optimal process or product conditions, supported by a polynomial model fitted to a structured experimental design.	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.