Comparer des méthodes

	Analyse de fiabilité assistée par optimisation	Planification d'Expériences
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s–2000s	1935
Auteur d'origine	Enevoldsen, Sørensen, Der Kiureghian (foundational RBDO formulations, 1990s)	Ronald A. Fisher
Type	Hybrid quantitative engineering method	Experimental planning framework
Source fondatrice	Haukaas, T., & Der Kiureghian, A. (2006). Strategies for finding the design point in non-linear finite element reliability analysis. Probabilistic Engineering Mechanics, 21(2), 133–147.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Alias	RBDO-coupled reliability analysis, optimization-integrated reliability assessment, reliability-based optimization, OA-RA	DOE, experimental design, factorial experimentation, planned experimentation
Apparentées	6	3
Résumé	Optimization-assisted reliability analysis couples probabilistic reliability assessment with mathematical optimization to simultaneously identify failure probabilities and find design configurations that satisfy reliability targets at minimum cost or weight. Widely applied in structural, mechanical, and aerospace engineering, it integrates methods such as FORM, SORM, or Monte Carlo simulation within an optimization loop so that design decisions are driven by quantified risk rather than deterministic safety factors alone.	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.