Salīdzināt metodes

	Analīze, ko atbalsta simulācija, izmantojot režīmu un seku analīzi	Statistiskā uzticamības analīze
Nozare	Eksperimentu plānošana	Drošums
Saime	Process / pipeline	Regression model
Izcelsmes gads	1949 (FMEA); simulation-assisted variant: 1980s–1990s	1998
Autors	FMEA originates from US MIL-P-1629 (1949); simulation integration developed in reliability engineering from the 1980s–1990s	William Meeker & Luis Escobar
Tips	Reliability and risk analysis method	Parametric lifetime modeling
Pirmavots	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Meeker, W. Q., & Escobar, L. A. (1998). Statistical Methods for Reliability Data. Wiley. ISBN: 978-0-471-14328-4
Citi nosaukumi	Simulation-FMEA, Monte Carlo FMEA, Simulation-based FMEA, SA-FMEA	Life Data Analysis, Survival Analysis (Engineering), Time-to-Failure Analysis, Güvenilirlik Analizi
Saistītās	6	3
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.	Statistical reliability analysis models the time-to-failure of components, systems, or products using parametric lifetime distributions fitted to observed or censored failure data. Formalized comprehensively by William Q. Meeker and Luis A. Escobar in their 1998 Wiley monograph, the framework integrates maximum likelihood estimation, censoring mechanisms, and distributional diagnostics to produce probability-of-failure curves, hazard rates, and quantile estimates that support design, warranty, and maintenance decisions.