Порівняння методів

	Методологія багатофакторних поверхонь відгуку	Планування експериментів
Галузь	Планування експерименту	Планування експерименту
Родина	Process / pipeline	Process / pipeline
Рік появи	1980 (Derringer & Suich desirability function); RSM roots ~1951 (Box & Wilson)	1935
Автор методу	Derringer & Suich (desirability function approach); Myers & Montgomery (RSM framework)	Ronald A. Fisher
Тип	Experimental optimization technique	Experimental planning framework
Основоположне джерело	Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Інші назви	Multi-response RSM, MRSM, Multi-objective RSM, Multiple response optimization	DOE, experimental design, factorial experimentation, planned experimentation
Пов'язані	6	3
Підсумок	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.	Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.