ScholarGate
Asystent

Porównaj metody

Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.

Symulacyjnie wspomagane frakcjonowane plany czynnikowe×Central Composite Design×
DziedzinaPlanowanie eksperymentówPlanowanie eksperymentów
RodzinaProcess / pipelineProcess / pipeline
Rok powstaniaFFD: 1950s; simulation integration: 1980s–2000s1951
TwórcaBox, Hunter & Hunter (FFD basis); Kleijnen and others (simulation integration)George E. P. Box and K. B. Wilson
TypExperimental design with computational augmentationResponse surface experimental design
Źródło pierwotneKleijnen, J. P. C. (2008). Design and Analysis of Simulation Experiments. Springer. ISBN: 978-0387718125Box, 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. DOI ↗
Inne nazwySA-FFD, virtual fractional factorial design, computer-aided fractional factorial design, simulation-based FFDCCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Pokrewne43
PodsumowanieSimulation-assisted fractional factorial design (SA-FFD) combines the statistical efficiency of fractional factorial experimentation with computerized simulation models to screen and estimate factor effects when physical experiments are too costly, hazardous, or time-consuming. A carefully chosen subset of factor-level combinations — the fractional factorial array — is executed inside a validated simulation model instead of (or alongside) a real process, dramatically reducing resource requirements while preserving the ability to identify main effects and low-order interactions.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.
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

Przejdź do wyszukiwania Pobierz slajdy

ScholarGatePorównaj metody: Simulation-assisted fractional factorial design · Central Composite Design. Pobrano 2026-06-19 z https://scholargate.app/pl/compare