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| Phân tích Chế độ Hỏng hóc và Ảnh hưởng Bayes× | Phân tích cây lỗi Bayes× | |
|---|---|---|
| Lĩnh vực | Thiết kế thí nghiệm | Thiết kế thí nghiệm |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1990s–2000s | 2001 (BFTA mapping); Bayesian networks: 1988 |
| Người khởi xướng≠ | Extension of classical FMEA (MIL-STD-1629, 1974) with Bayesian inference formalised in reliability literature from the 1990s onward | Andrea Bobbio, Luca Portinale et al. (mapping FTA to Bayesian networks); Judea Pearl (Bayesian networks) |
| Loại≠ | Probabilistic reliability and risk analysis | Probabilistic reliability / safety analysis |
| Công trình gốc≠ | Bowles, J. B., & Peláez, C. E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering and System Safety, 50(2), 203–213. DOI ↗ | Bobbio, A., Portinale, L., Minichino, M., & Ciancamerla, E. (2001). Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliability Engineering & System Safety, 71(3), 249–260. DOI ↗ |
| Tên gọi khác | Bayesian FMEA, probabilistic FMEA, B-FMEA, Bayesian risk priority analysis | BFTA, Bayesian FTA, Bayesian network fault tree, probabilistic fault tree analysis |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Bayesian FMEA extends the classical Failure Mode and Effects Analysis framework by replacing fixed point-estimate risk scores with probability distributions, allowing prior engineering knowledge and observed failure data to be formally combined through Bayes' theorem. The result is a probabilistic Risk Priority Number (RPN) that reflects uncertainty in severity, occurrence, and detectability ratings rather than masking it with single consensus values. | Bayesian Fault Tree Analysis (BFTA) extends classical fault tree analysis by converting the fault tree structure into an equivalent Bayesian network, enabling probabilistic inference in both forward (prediction) and backward (diagnosis) directions. This integration allows analysts to update failure probability estimates with observed evidence, quantify uncertainty explicitly, and identify the most probable root causes of a top-level system failure. |
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