Comparar métodos

	Delineamento Box-Behnken Baseado em Risco	Delineamento Box-Behnken
Área	Delineamento experimental	Delineamento experimental
Família	Process / pipeline	Process / pipeline
Ano de origem	2005–2009 (QbD-era integration of risk assessment with BBD)	1960
Autor original	Box & Behnken (BBD, 1960); risk integration formalized under ICH Q8/Q9 pharmaceutical QbD frameworks (~2005–2009)	George E. P. Box and Donald W. Behnken
Tipo	Response surface experimental design with risk prioritization	Response surface design (incomplete three-level factorial)
Fonte seminal	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Outros nomes	Risk-based BBD, Risk-prioritized Box-Behnken, QbD Box-Behnken design, Risk-informed RSM	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Relacionados	4	3
Resumo	Risk-based Box-Behnken Design combines the classical three-level Box-Behnken response surface design with a formal risk assessment step — typically a risk ranking tool such as FMEA or Ishikawa analysis — to prioritize which process or formulation factors deserve experimental investigation. Widely adopted in pharmaceutical Quality by Design (QbD) and engineering process optimization, the approach ensures that experimental resources are directed toward the factor combinations most likely to affect product quality or process performance, reducing unnecessary runs while preserving predictive power.	The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test.