Compară metode

	Dezvoltarea funcției de calitate asistată de optimizare	Deploierea Robusta a Funcției Calității
Domeniu	Design experimental	Design experimental
Familie	Process / pipeline	Process / pipeline
Anul apariției	1990s–2000s (QFD base: ~1966)	2000s (robust extensions of QFD originating 1966)
Autorul original	Yoji 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)
Tip	Integrated engineering design method	Hybrid quality-engineering planning method
Sursa seminală	Akao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press, Cambridge, MA. ISBN: 978-0915299416	Fung, 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.
Denumiri alternative	Optimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFD	Robust QFD, Uncertainty-tolerant QFD, Fuzzy-robust QFD, Robust House of Quality
Înrudite	4	4
Rezumat	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.	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.