Σύγκριση μεθόδων

	Ανάλυση Αξιοπιστίας με Υποβοήθηση Προσομοίωσης	Προσομοίωση Monte Carlo
Πεδίο	Πειραματικός Σχεδιασμός	Λήψη Αποφάσεων
Οικογένεια	Process / pipeline	MCDM
Έτος προέλευσης	1940s–1980s (Monte Carlo foundations ~1940s; simulation-reliability integration ~1970s–1980s)	1949
Δημιουργός	Enrico Fermi, John von Neumann, Stanislaw Ulam (Monte Carlo foundations); Freudenthal (structural reliability); Melchers (simulation integration)	Metropolis, N., Ulam, S.
Τύπος	Quantitative probabilistic engineering method	Robustness wrapper — Monte Carlo uncertainty propagation
Θεμελιώδης πηγή	Melchers, R. E., & Beck, A. T. (2018). Structural Reliability Analysis and Prediction (3rd ed.). Wiley. ISBN: 978-1119266075	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Εναλλακτικές ονομασίες	SARA, Monte Carlo reliability analysis, simulation-based reliability assessment, virtual reliability testing	—
Συναφείς	6	0
Σύνοψη	Simulation-assisted reliability analysis combines probabilistic reliability theory with computational simulation — most commonly Monte Carlo methods or finite-element models — to estimate the probability that a system, component, or structure will perform its intended function under uncertain operating conditions. Rather than relying solely on closed-form analytical solutions, it propagates uncertainty through high-fidelity numerical models to quantify failure risk across complex, nonlinear, or multi-failure-mode systems.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.