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Hybrid Quality Function Deployment×Proiectarea Experimentelor×
DomeniuDesign experimentalDesign experimental
FamilieProcess / pipelineProcess / pipeline
Anul apariției1966 (QFD foundation); hybrid variants from mid-1990s onward1935
Autorul originalYoji Akao (QFD foundation); hybrid extensions by various authors integrating fuzzy sets, AHP, TOPSIS, and optimizationRonald A. Fisher
TipIntegrated engineering design and decision methodExperimental planning framework
Sursa seminalăAkao, Y. (Ed.). (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press. ISBN: 978-0915299416Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Denumiri alternativeHybrid QFD, Integrated QFD, QFD hybrid approach, Extended Quality Function DeploymentDOE, experimental design, factorial experimentation, planned experimentation
Înrudite43
RezumatHybrid Quality Function Deployment (Hybrid QFD) extends the classic House of Quality framework by embedding additional analytical techniques — such as fuzzy set theory, Analytic Hierarchy Process, TOPSIS, or optimization algorithms — directly into the QFD pipeline. This integration addresses known weaknesses of standard QFD, such as imprecision in customer ratings and subjectivity in relationship matrices, while preserving the method's core strength: systematically translating the voice of the customer into actionable engineering specifications.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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  1. v1
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  3. PUBLISHED

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ScholarGateCompară metode: Hybrid Quality Function Deployment · Design of experiments. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare