ScholarGate
Asistent

Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Optimalizace v rámci QFD×Robustní nasazení funkcí kvality×
OborPlánování experimentůPlánování experimentů
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1990s–2000s (QFD base: ~1966)2000s (robust extensions of QFD originating 1966)
TvůrceYoji Akao (QFD); optimization extensions by various researchers (1990s–2000s)Extension of Yoji Akao's QFD (1966); robust adaptation by Fung, Kwong and others (early 2000s)
TypIntegrated engineering design methodHybrid quality-engineering planning method
Původní zdrojAkao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press, Cambridge, MA. ISBN: 978-0915299416Fung, R. Y. K., Tang, J., & Tu, Y. (2002). Modeling of quality function deployment planning under resource allocation constraints. Computers & Industrial Engineering, 43(1–2), 313–328. link ↗
Další názvyOptimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFDRobust QFD, Uncertainty-tolerant QFD, Fuzzy-robust QFD, Robust House of Quality
Příbuzné44
ShrnutíOptimization-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.Robust Quality Function Deployment (Robust QFD) extends the classical House of Quality framework by explicitly modeling uncertainty and variability in customer requirements, perception ratings, and engineering correlation judgments. Instead of treating inputs as crisp single-point values, it applies fuzzy sets, interval analysis, or Taguchi-inspired robustness techniques to ensure that the resulting design targets remain stable and customer-satisfying even when inputs are imprecise or fluctuating.
ScholarGateDatová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Přejít na hledání Stáhnout prezentaci

ScholarGatePorovnat metody: Optimization-assisted quality function deployment · Robust Quality Function Deployment. Získáno 2026-06-15 z https://scholargate.app/cs/compare