Comparar métodos

	Despliegue de la Función de Calidad Asistido por Optimización	Diseño de Experimentos
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Process / pipeline
Año de origen	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
Fuente 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.
Alias	Optimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFD	DOE, experimental design, factorial experimentation, planned experimentation
Relacionados	4	3
Resumen	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.