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Optymalizacja wspomagana wdrożeniem funkcji jakości×Projektowanie Doświadczeń×
DziedzinaPlanowanie eksperymentówPlanowanie eksperymentów
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1990s–2000s (QFD base: ~1966)1935
TwórcaYoji Akao (QFD); optimization extensions by various researchers (1990s–2000s)Ronald A. Fisher
TypIntegrated engineering design methodExperimental planning framework
Źródło pierwotneAkao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press, Cambridge, MA. ISBN: 978-0915299416Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Inne nazwyOptimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFDDOE, experimental design, factorial experimentation, planned experimentation
Pokrewne43
PodsumowanieOptimization-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.
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ScholarGatePorównaj metody: Optimization-assisted quality function deployment · Design of experiments. Pobrano 2026-06-17 z https://scholargate.app/pl/compare