เปรียบเทียบวิธี

	การวิเคราะห์แผนภูมิต้นไม้แห่งความผิดพร่องด้วยการจำลองสถานการณ์	การวิเคราะห์แผนภูมิต้นไม้ความผิดพลาดตามความเสี่ยง
สาขาวิชา	การออกแบบการทดลอง	การออกแบบการทดลอง
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1970s–1980s (widespread adoption in nuclear and aerospace industries)	1961 (FTA origin); risk-based integration formalised 1975–1981
ผู้ริเริ่ม	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	H.A. Watson (Bell Labs) and developed further by Boeing/U.S. Air Force; risk-based extension via NRC probabilistic risk assessment programs
ประเภท	Quantitative reliability and risk analysis technique	Quantitative safety and reliability analysis
แหล่งต้นตำรับ	Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. US Nuclear Regulatory Commission, NUREG-0492.	Vesely, W. E., Goldberg, F. F., Roberts, N. H., & Haasl, D. F. (1981). Fault Tree Handbook. U.S. Nuclear Regulatory Commission, NUREG-0492.
ชื่อเรียกอื่น	SA-FTA, Monte Carlo FTA, simulation-based FTA, stochastic fault tree analysis	RB-FTA, risk-informed FTA, quantitative fault tree analysis, probabilistic fault tree analysis
ที่เกี่ยวข้อง	6	6
สรุป	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.	Risk-based fault tree analysis (RB-FTA) combines classical fault tree analysis with explicit quantitative risk assessment. Starting from an undesired top event, the analyst decomposes it into contributing causes using AND/OR logic gates, assigns failure probabilities to basic events from reliability databases or historical data, and then propagates those probabilities through the tree to compute top-event likelihood. The result is expressed as risk — probability weighted by consequence severity — enabling prioritisation of safety interventions by their actual risk reduction impact.