Сравнение методов

	Анализ чувствительности с FMEA	Статистическое управление процессами
Область	Планирование эксперимента	Планирование эксперимента
Семейство	Process / pipeline	Process / pipeline
Год появления	1990s–2000s (systematic integration)	1924–1931
Автор метода	Grumman Aircraft (FMEA origin, 1950s); sensitivity analysis integration developed by reliability engineering community	Walter A. Shewhart
Тип	Hybrid risk analysis and sensitivity technique	Process monitoring and quality control method
Основополагающий источник	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Другие названия	SA-FMEA, FMEA with sensitivity analysis, sensitivity-enhanced FMEA, SA-integrated FMEA	SPC, statistical quality control, process control charting, Shewhart control
Связанные	6	6
Сводка	Sensitivity analysis with failure mode and effects analysis (SA-FMEA) combines classical FMEA risk scoring with systematic sensitivity analysis to determine which input parameters — severity, occurrence, and detectability ratings — drive the Risk Priority Number (RPN) most strongly. This integration helps teams focus improvement resources where they matter most, revealing how uncertain or variable scoring assumptions propagate into final risk rankings.	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.