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	Pełne projektowanie czynnikowe wspomagane symulacją	Central Composite Design
Dziedzina	Planowanie eksperymentów	Planowanie eksperymentów
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1990s–2000s (simulation-DOE integration formalized)	1951
Twórca	Montgomery (DOE foundations); Kleijnen (simulation DOE formalization)	George E. P. Box and K. B. Wilson
Typ	Experimental design with computer simulation	Response surface experimental design
Źródło pierwotne	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.
Inne nazwy	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
Pokrewne	4	3
Podsumowanie	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.