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| Robuste Fehlermöglichkeits- und Einflussanalyse (Robust FMEA)× | Fehlerbaumanalyse (FTA)× | |
|---|---|---|
| Fachgebiet≠ | Versuchsplanung | Reliabilität |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1980s–1990s | 1981 |
| Urheber≠ | Extension of traditional FMEA (MIL-P-1629, 1949) integrated with Taguchi robust design philosophy (Genichi Taguchi, 1980s) | Vesely et al. (US NRC Fault Tree Handbook) |
| Typ≠ | Risk analysis with variability quantification | Deductive top-down failure analysis |
| Wegweisende Quelle≠ | Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989 | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook (NUREG-0492). U.S. Nuclear Regulatory Commission. link ↗ |
| Aliasnamen | Robust FMEA, Noise-Aware FMEA, Variability-Integrated FMEA, Robustness-Based FMEA | FTA, Fault Tree Method, Top-Down Reliability Analysis, Hata Ağacı Analizi |
| Verwandt≠ | 4 | 3 |
| Zusammenfassung≠ | Robust Failure Mode and Effects Analysis extends the classical FMEA framework by explicitly incorporating noise factors, parameter variability, and environmental variation into the risk assessment process. Rather than treating failure likelihood as a single deterministic estimate, it uses robust design principles — most notably from Taguchi's quality engineering — to evaluate how process variability and uncontrollable noise factors influence the probability and severity of each failure mode, yielding risk priority numbers that reflect real-world variability. | Fault Tree Analysis (FTA) is a top-down, deductive reliability method that begins with an undesired top-level failure event and systematically traces backward through chains of contributing causes using Boolean logic gates (AND, OR). First formalized by Watson at Bell Telephone Laboratories in 1961 and later standardized by Vesely, Goldberg, Roberts, and Haasl in the landmark 1981 NRC Fault Tree Handbook, FTA has become a cornerstone of quantitative risk assessment in nuclear, aerospace, and industrial safety engineering. |
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