Methoden vergleichen

	Robuste Response-Surface-Methodologie	Box-Behnken-Design
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1990	1960
Urheber	G. G. Vining and Raymond H. Myers (dual response formulation)	George E. P. Box and Donald W. Behnken
Typ	Experimental optimization technique	Response surface design (incomplete three-level factorial)
Wegweisende Quelle	Vining, G. G., & Myers, R. H. (1990). Combining Taguchi and response surface philosophies: A dual response approach. Journal of Quality Technology, 22(1), 38–45.	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	Robust RSM, dual response surface methodology, robust parameter design via RSM, mean-variance RSM	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Verwandt	3	3
Zusammenfassung	Robust Response Surface Methodology (Robust RSM) is an experimental optimization strategy that simultaneously fits two regression models — one for the mean response and one for its variance (or standard deviation) — across a designed experiment. By jointly optimizing these dual surfaces, engineers identify factor settings that hit a performance target while minimizing process variability, combining the empirical model-building power of classical RSM with the variance-reduction goals of robust parameter 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.