Salīdzināt metodes

	Analīze, ko atbalsta simulācija, izmantojot režīmu un seku analīzi	Monte Carlo simulācija
Nozare	Eksperimentu plānošana	Lēmumu pieņemšana
Saime	Process / pipeline	MCDM
Izcelsmes gads	1949 (FMEA); simulation-assisted variant: 1980s–1990s	1949
Autors	FMEA originates from US MIL-P-1629 (1949); simulation integration developed in reliability engineering from the 1980s–1990s	Metropolis, N., Ulam, S.
Tips	Reliability and risk analysis method	Robustness wrapper — Monte Carlo uncertainty propagation
Pirmavots	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Citi nosaukumi	Simulation-FMEA, Monte Carlo FMEA, Simulation-based FMEA, SA-FMEA	—
Saistītās	6	0
Kopsavilkums	Simulation-assisted FMEA enhances the classical Failure Mode and Effects Analysis by replacing point-estimate occurrence ratings with probabilistic simulation — typically Monte Carlo — to quantify failure probability distributions across a system's components. This yields statistically grounded Risk Priority Numbers (RPNs) rather than expert guesses, enabling more rigorous identification and prioritization of critical failure modes in complex engineering 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.