Comparar métodos

	Quality Function Deployment Assistida por Otimização	Desenho de Experimentos
Área	Delineamento experimental	Delineamento experimental
Família	Process / pipeline	Process / pipeline
Ano de origem	1990s–2000s (QFD base: ~1966)	1935
Autor original	Yoji Akao (QFD); optimization extensions by various researchers (1990s–2000s)	Ronald A. Fisher
Tipo	Integrated engineering design method	Experimental planning framework
Fonte seminal	Akao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press, Cambridge, MA. ISBN: 978-0915299416	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Outros nomes	Optimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFD	DOE, experimental design, factorial experimentation, planned experimentation
Relacionados	4	3
Resumo	Optimization-assisted QFD extends the classic House of Quality framework by embedding mathematical optimization — linear programming, multi-objective optimization, or metaheuristics — directly into the QFD process. This allows engineers to simultaneously maximize customer satisfaction and minimize cost or resource constraints when setting target values for engineering characteristics, going beyond the largely subjective priority rankings of traditional QFD.	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.