Comparar métodos

	Design Fatorial Completo Baseado em Risco	Desenho de Experimentos
Área	Delineamento experimental	Delineamento experimental
Família	Process / pipeline	Process / pipeline
Ano de origem	2000s (formal integration with risk frameworks circa 2005–2009)	1935
Autor original	Developed at the intersection of classical factorial experimentation (Fisher, 1935) and formal risk analysis frameworks (ICH Q8/Q9, 2005–2009)	Ronald A. Fisher
Tipo	Structured experimental design with risk-informed factor prioritization	Experimental planning framework
Fonte seminal	Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Outros nomes	risk-informed full factorial design, RB-FFD, risk-prioritized factorial experiment, risk-based FFD	DOE, experimental design, factorial experimentation, planned experimentation
Relacionados	3	3
Resumo	Risk-based full factorial design integrates formal risk analysis — typically Failure Mode and Effects Analysis (FMEA) or a comparable risk-ranking tool — with a full factorial experiment to ensure that factors posing the greatest quality or safety risk receive exhaustive experimental coverage. All combinations of selected factor levels are run, but the selection of which factors to include and the range of their levels is explicitly guided by prior risk scores rather than purely by engineering intuition or resource availability.	Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.