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| Analisis Punca Asas Dibantu Simulasi× | Analisis Pohon Kegagalan Dibantu Simulasi× | |
|---|---|---|
| Bidang | Reka Bentuk Eksperimen | Reka Bentuk Eksperimen |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1990s–2000s (widespread adoption in engineering reliability contexts) | 1970s–1980s (widespread adoption in nuclear and aerospace industries) |
| Pengasas≠ | Evolved from root cause analysis practice (Kepner & Tregoe, 1960s) integrated with simulation methods (1990s–2000s in reliability engineering) | 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 |
| Jenis≠ | Analytical / diagnostic engineering method | Quantitative reliability and risk analysis technique |
| Sumber perintis≠ | Latino, R. J., & Latino, K. C. (2006). Root Cause Analysis: Improving Performance for Bottom-Line Results (3rd ed.). CRC Press. ISBN: 978-0849338267 | Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. US Nuclear Regulatory Commission, NUREG-0492. link ↗ |
| Alias | Sim-RCA, simulation-based RCA, virtual root cause analysis, computational root cause analysis | SA-FTA, Monte Carlo FTA, simulation-based FTA, stochastic fault tree analysis |
| Berkaitan | 6 | 6 |
| Ringkasan≠ | Simulation-assisted root cause analysis (Sim-RCA) integrates computational simulation — such as discrete-event simulation, Monte Carlo methods, or finite-element analysis — into the structured root cause analysis process to diagnose the underlying causes of complex failures or defects. By running virtual experiments on a system model, investigators can test hypothetical causal pathways safely, rapidly, and at scale, without disrupting live operations or waiting for rare failure events to recur. | 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. |
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