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| Simulationsgestützte Fehlerursachen- und Wirkungsanalyse× | Monte-Carlo-Simulation× | |
|---|---|---|
| Fachgebiet≠ | Versuchsplanung | Entscheidungsfindung |
| Familie≠ | Process / pipeline | MCDM |
| Entstehungsjahr≠ | 1949 (FMEA); simulation-assisted variant: 1980s–1990s | 1949 |
| Urheber≠ | FMEA originates from US MIL-P-1629 (1949); simulation integration developed in reliability engineering from the 1980s–1990s | Metropolis, N., Ulam, S. |
| Typ≠ | Reliability and risk analysis method | Robustness wrapper — Monte Carlo uncertainty propagation |
| Wegweisende Quelle≠ | 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 DOI ↗ |
| Aliasnamen≠ | Simulation-FMEA, Monte Carlo FMEA, Simulation-based FMEA, SA-FMEA | — |
| Verwandt≠ | 6 | 0 |
| Zusammenfassung≠ | 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. |
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