Krahasoni metodat

	Analiza e Ndjeshmërisë me Analizën e Besueshmërisë	Analiza e ndjeshmërisë me Analizën e Pemës së Defekteve
Fusha	Dizajni eksperimental	Dizajni eksperimental
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1969 (importance measures); 2000s (global SA integration)	1961 (FTA); sensitivity integration formalised 1970s–1980s
Krijuesi	Birnbaum (importance measures, 1969); Saltelli et al. (global SA formalization, 2000s)	H. A. Watson (Bell Labs, FTA, 1961); integrated sensitivity extensions developed through nuclear safety research (Vesely et al., 1981)
Lloji	Quantitative integrated engineering method	Quantitative reliability and risk analysis technique
Burimi themelues	Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 978-0470059975	Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. US Nuclear Regulatory Commission, NUREG-0492.
Emërtime të tjera	SA-RA, reliability sensitivity analysis, importance measures in reliability, reliability-based sensitivity analysis	FTA-SA, fault tree sensitivity analysis, FTA with importance measures, probabilistic sensitivity analysis in fault trees
Të lidhura	5	3
Përmbledhja	Sensitivity analysis integrated with reliability analysis is a quantitative engineering method that determines how uncertainty or variation in each system input — such as component failure rates, material properties, or load distributions — propagates into overall system reliability. By computing importance measures for every uncertain parameter, analysts can rank components and assumptions by their influence on system dependability, focusing improvement efforts where they matter most.	Sensitivity analysis integrated with fault tree analysis (FTA-SA) is a quantitative reliability engineering method that first models how system failure can occur through a hierarchical Boolean logic tree, then systematically varies the probability of each basic event to determine which components drive overall system failure risk most strongly. Widely used in nuclear, aerospace, chemical, and safety-critical system design, it prioritises mitigation effort and reveals which uncertainty in input data matters most.