방법 비교

	실험계획법 기반 위험 평가	고장 모드 및 영향 분석 (FMEA)
분야	실험설계	실험설계
계열	Process / pipeline	Process / pipeline
기원 연도	2000s–2010s (formalized in pharmaceutical and process engineering contexts)	1949 (military); widespread industrial adoption 1970s–1980s
창시자	Emerged from ICH Q8/Q9/Q10 pharmaceutical guidelines; formalized in engineering by integration of FMEA/FTA with classical DoE	U.S. Military / NASA (formalized by MIL-P-1629, 1949)
유형	Experimental design method with risk-based factor prioritization	Proactive risk analysis technique
원전	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916018	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989
별칭	Risk-based DoE, risk-informed experimental design, risk-prioritized DoE, RB-DoE	FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis
관련	4	6
요약	Risk-based design of experiments (RB-DoE) integrates formal risk assessment — typically using tools such as FMEA or fault tree analysis — with classical experimental design to prioritize which process or product factors are most critical to investigate. Rather than treating all candidate factors equally, this approach ranks factors by their risk priority number or likelihood of affecting quality, safety, or reliability, then allocates experimental runs preferentially to high-risk factors. It is widely used in pharmaceutical development, chemical process engineering, and manufacturing quality management.	Failure Mode and Effects Analysis (FMEA) is a structured, proactive risk management technique used to identify potential failure modes in a system, process, or product design, evaluate their consequences, and prioritize corrective actions before failures occur. Originally developed for the U.S. military in 1949 and later adopted by NASA, automotive, and manufacturing industries, FMEA is now a cornerstone quality-engineering tool embedded in standards such as AIAG-VDA and ISO 9001-aligned processes.