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| Analisis Pohon Kegagalan Dibantu Simulasi× | Analisis Kebolehpercayaan Statistik× | |
|---|---|---|
| Bidang≠ | Reka Bentuk Eksperimen | Kebolehpercayaan |
| Keluarga≠ | Process / pipeline | Regression model |
| Tahun asal≠ | 1970s–1980s (widespread adoption in nuclear and aerospace industries) | 1998 |
| Pengasas≠ | Fault tree analysis: H. A. Watson (Bell Labs, 1961); Monte Carlo integration in reliability: Herman Kahn / Stanislaw Ulam (RAND, late 1940s); combination formalized in reliability engineering literature from the 1970s onward | William Meeker & Luis Escobar |
| Jenis≠ | Quantitative reliability and risk analysis technique | Parametric lifetime modeling |
| Sumber perintis≠ | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. US Nuclear Regulatory Commission, NUREG-0492. link ↗ | Meeker, W. Q., & Escobar, L. A. (1998). Statistical Methods for Reliability Data. Wiley. ISBN: 978-0-471-14328-4 |
| Alias | SA-FTA, Monte Carlo FTA, simulation-based FTA, stochastic fault tree analysis | Life Data Analysis, Survival Analysis (Engineering), Time-to-Failure Analysis, Güvenilirlik Analizi |
| Berkaitan≠ | 6 | 3 |
| Ringkasan≠ | Simulation-assisted fault tree analysis (SA-FTA) combines the logical structure of classical fault tree analysis with Monte Carlo or discrete-event simulation to estimate the probability and timing of an undesired top event when component failures follow complex, non-exponential, or correlated probability distributions. The approach overcomes the analytical limitations of Boolean algebra-based FTA and is widely used in nuclear, aerospace, chemical process, and manufacturing reliability engineering. | 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. |
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