Σύγκριση μεθόδων

	Σχεδιασμός Κλασματικού Παραγοντικού Πειράματος με Υποβοήθηση Προσομοίωσης	Σχεδιασμός Πειραμάτων
Πεδίο	Πειραματικός Σχεδιασμός	Πειραματικός Σχεδιασμός
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	FFD: 1950s; simulation integration: 1980s–2000s	1935
Δημιουργός	Box, Hunter & Hunter (FFD basis); Kleijnen and others (simulation integration)	Ronald A. Fisher
Τύπος	Experimental design with computational augmentation	Experimental planning framework
Θεμελιώδης πηγή	Kleijnen, J. P. C. (2008). Design and Analysis of Simulation Experiments. Springer. ISBN: 978-0387718125	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Εναλλακτικές ονομασίες	SA-FFD, virtual fractional factorial design, computer-aided fractional factorial design, simulation-based FFD	DOE, experimental design, factorial experimentation, planned experimentation
Συναφείς	4	3
Σύνοψη	Simulation-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.	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.