Methoden vergleichen

	Simulation-unterstütztes vollständiges faktorielles Design	Design of Experiments
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1990s–2000s (simulation-DOE integration formalized)	1935
Urheber	Montgomery (DOE foundations); Kleijnen (simulation DOE formalization)	Ronald A. Fisher
Typ	Experimental design with computer simulation	Experimental planning framework
Wegweisende Quelle	Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Aliasnamen	SA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOE	DOE, experimental design, factorial experimentation, planned experimentation
Verwandt	4	3
Zusammenfassung	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.	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.