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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Simulatie-ondersteund Volledig Factorieel Ontwerp×Experimenteel Ontwerp×
VakgebiedExperimenteel ontwerpExperimenteel ontwerp
FamilieProcess / pipelineProcess / pipeline
Jaar van ontstaan1990s–2000s (simulation-DOE integration formalized)1935
GrondleggerMontgomery (DOE foundations); Kleijnen (simulation DOE formalization)Ronald A. Fisher
TypeExperimental design with computer simulationExperimental planning framework
Oorspronkelijke bronMontgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
AliassenSA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOEDOE, experimental design, factorial experimentation, planned experimentation
Verwant43
SamenvattingSimulation-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.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.
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ScholarGateMethoden vergelijken: Simulation-assisted full factorial design · Design of experiments. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare