Salīdzināt metodes

	Vairākuzdevumu atbildes virsmas metodoloģija	Box-Behnkena dizains
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1980 (Derringer & Suich desirability function); RSM roots ~1951 (Box & Wilson)	1960
Autors	Derringer & Suich (desirability function approach); Myers & Montgomery (RSM framework)	George E. P. Box and Donald W. Behnken
Tips	Experimental optimization technique	Response surface design (incomplete three-level factorial)
Pirmavots	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.
Citi nosaukumi	Multi-response RSM, MRSM, Multi-objective RSM, Multiple response optimization	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Saistītās	6	3
Kopsavilkums	Multi-response Response Surface Methodology (MRSM) extends classical RSM to situations where an experiment generates two or more response variables that must be optimized simultaneously. Rather than tuning factor settings for a single output, MRSM fits a separate second-order polynomial model for each response, then combines them — most commonly via Derringer and Suich's desirability function — to find factor settings that satisfy all objectives at once.	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.