手法を比較

	ベイズ的故障モード影響解析 (Bayesian Failure Mode and Effects Analysis)	統計的プロセス管理
分野	実験計画法	実験計画法
系統	Process / pipeline	Process / pipeline
提唱年	1990s–2000s	1924–1931
提唱者	Extension of classical FMEA (MIL-STD-1629, 1974) with Bayesian inference formalised in reliability literature from the 1990s onward	Walter A. Shewhart
種類	Probabilistic reliability and risk analysis	Process monitoring and quality control method
原典	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.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
別名	Bayesian FMEA, probabilistic FMEA, B-FMEA, Bayesian risk priority analysis	SPC, statistical quality control, process control charting, Shewhart control
関連	5	6
概要	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.	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.