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Déploiement de la Qualité assisté par Optimisation×Planification d'Expériences×
DomainePlans d'expériencesPlans d'expériences
FamilleProcess / pipelineProcess / pipeline
Année d'origine1990s–2000s (QFD base: ~1966)1935
Auteur d'origineYoji Akao (QFD); optimization extensions by various researchers (1990s–2000s)Ronald A. Fisher
TypeIntegrated engineering design methodExperimental planning framework
Source fondatriceAkao, 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 ↗
AliasOptimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFDDOE, experimental design, factorial experimentation, planned experimentation
Apparentées43
RésuméOptimization-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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ScholarGateComparer des méthodes: Optimization-assisted quality function deployment · Design of experiments. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare