Сравнение методов

	Симуляционное полнофакторное планирование	Центральное композиционное планирование
Область	Планирование эксперимента	Планирование эксперимента
Семейство	Process / pipeline	Process / pipeline
Год появления	1990s–2000s (simulation-DOE integration formalized)	1951
Автор метода	Montgomery (DOE foundations); Kleijnen (simulation DOE formalization)	George E. P. Box and K. B. Wilson
Тип	Experimental design with computer simulation	Response surface experimental design
Основополагающий источник	Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478	Box, G. E. P., & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society: Series B, 13(1), 1–45.
Другие названия	SA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOE	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Связанные	4	3
Сводка	Simulation-assisted full factorial design integrates full factorial design of experiments (DOE) with computer simulation models — such as discrete-event simulation, finite element analysis, or Monte Carlo methods — to systematically explore every combination of factor levels and quantify their effects on system responses. It enables comprehensive experimentation in contexts where physical trials would be costly, dangerous, or infeasible.	Central Composite Design (CCD) is a second-order response surface design that allows researchers to efficiently fit a full quadratic model relating multiple continuous input factors to one or more response variables. Introduced by Box and Wilson in 1951, it combines a factorial (or fractional factorial) core, axial (star) points, and center-point replicates into a single unified design, making it the most widely used design for process optimization in engineering, chemistry, and manufacturing.