Módszerek összehasonlítása

	Több válasz eseményfa-elemzés	Statisztikai folyamatszabályozás
Tudományterület	Kísérlettervezés	Kísérlettervezés
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1975 (ETA); multi-response extension: 1990s–2000s	1924–1931
Megalkotó	Developed from Event Tree Analysis (originated at WASH-1400 nuclear safety study, U.S. Nuclear Regulatory Commission, 1975); multi-response extension adapted from design-of-experiments and reliability engineering practice	Walter A. Shewhart
Típus	Probabilistic safety and reliability analysis with multiple simultaneous response outcomes	Process monitoring and quality control method
Alapmű	Stamatelatos, M., Vesely, W., Dugan, J., Fragola, J., Minarick, J., & Railsback, J. (2002). Fault Tree Handbook with Aerospace Applications. NASA Office of Safety and Mission Assurance.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Alternatív nevek	MR-ETA, multi-output event tree analysis, multi-response ETA, probabilistic event tree with multiple responses	SPC, statistical quality control, process control charting, Shewhart control
Kapcsolódó	5	6
Összefoglaló	Multi-response Event Tree Analysis (MR-ETA) extends classical event tree analysis by simultaneously tracking multiple system performance or safety response variables across all accident sequences. Instead of evaluating a single outcome (e.g., probability of failure), it propagates several concurrent response metrics — such as damage severity, downtime, cost, and environmental impact — through the event tree branches, enabling richer risk characterization and trade-off decisions under a single probabilistic framework.	Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers.