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| Хибриден анализ на дърво на отказите× | Диаграма на блокове за надеждност× | |
|---|---|---|
| Област≠ | Планиране на експеримента | Оперативен мениджмънт |
| Семейство≠ | Process / pipeline | Machine learning |
| Година на възникване≠ | 1983–2001 (multiple extensions) | 2010 |
| Създател≠ | Tanaka et al. (fuzzy extension, 1983); Bobbio et al. (Bayesian integration, 2001) | Ebeling, C. E. |
| Тип≠ | Quantitative safety and reliability analysis method | Reliability analysis technique |
| Основополагащ източник≠ | Tanaka, H., Fan, L. T., Lai, F. S., & Toguchi, K. (1983). Fault-tree analysis by fuzzy probability. IEEE Transactions on Reliability, 32(5), 453–457. DOI ↗ | Ebeling, C. E. (2010). An introduction to reliability and maintainability engineering (2nd ed.). Long Grove, IL: Waveland Press. link ↗ |
| Други названия≠ | Hybrid FTA, Fuzzy-Bayesian FTA, Extended Fault Tree Analysis, Integrated FTA | RBD, reliability analysis |
| Свързани | 5 | 5 |
| Резюме≠ | Hybrid Fault Tree Analysis (Hybrid FTA) extends classical Fault Tree Analysis by integrating complementary modelling paradigms — most commonly fuzzy set theory, Bayesian networks, or event-tree logic — to overcome the strict data requirements and static assumptions of traditional FTA. The hybrid approach allows analysts to handle uncertainty in failure probability estimates, capture dynamic dependencies between components, and update risk assessments as new evidence becomes available, making it especially valuable in complex engineering systems where complete statistical failure data are rarely available. | A Reliability Block Diagram (RBD) is a visual representation of a system's architecture that models how component reliabilities combine to determine overall system reliability. Each block represents a component or subsystem with a known reliability (probability of functioning without failure), and connections between blocks represent functional relationships (series, parallel, or mixed). RBD analysis is a fundamental tool in reliability engineering, used to identify critical components, optimize redundancy, and predict system-level failure rates. |
| ScholarGateНабор от данни ↗ |
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