Comparer des méthodes

	Analyse Robuste d'Arbre de Défaillances	Arbre d'événements (ETA)
Domaine	Plans d'expériences	Fiabilité
Famille	Process / pipeline	Process / pipeline
Année d'origine	1980s–2000s (robustness extensions to classical FTA ca. 1961)	2002
Auteur d'origine	Extended from classical FTA (Watson, 1961; Bell Labs / U.S. Air Force); robustness extensions developed through reliability engineering and uncertainty quantification research from the 1980s onward	Andrews & Moss
Type	Quantitative reliability and safety analysis with uncertainty propagation	Forward inductive logic tree
Source fondatrice	Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. U.S. Nuclear Regulatory Commission, NUREG-0492.	Andrews, J. D., & Moss, T. R. (2002). Reliability and Risk Assessment (2nd ed.). Professional Engineering Publishing. ISBN: 978-1-86058-290-5
Alias	Robust FTA, Uncertainty-aware FTA, FTA with interval analysis, Imprecise probability FTA	ETA, Event Sequence Diagram Analysis, Initiating Event Analysis, Olay Ağacı Analizi
Apparentées	6	2
Résumé	Robust Fault Tree Analysis (Robust FTA) extends classical fault tree analysis by explicitly representing and propagating uncertainty in component failure probabilities. Rather than assigning single point estimates to basic events, it uses probability distributions, interval bounds, or imprecise probabilities, then propagates these through the logical tree structure to obtain bounds or distributions on the top-event failure probability. This makes risk conclusions defensible under incomplete or variable data.	Event Tree Analysis (ETA) is a forward inductive technique used in reliability and risk engineering to model the possible outcomes that follow an initiating event. Starting from a single undesired event, ETA traces all subsequent event sequences through a binary branching tree representing the success or failure of safety barriers and protective systems. Introduced formally in reliability and risk literature by Andrews and Moss (2002), it is widely applied in nuclear, chemical, and aerospace industries to quantify accident sequence probabilities and guide safety decision-making.