方法对比

	贝叶斯质量功能展开	实验设计
领域	实验设计	实验设计
方法族	Process / pipeline	Process / pipeline
起源年份	QFD: 1966–1972; Bayesian QFD extensions: 2000s–present	1935
提出者	Yoji Akao (QFD); Bayesian extension developed by multiple researchers including Fung, Tang, and colleagues	Ronald A. Fisher
类型	Probabilistic customer-driven design planning method	Experimental planning framework
开创性文献	Tang, J., Fung, R. Y. K., Xu, B., & Wang, D. (2002). A new approach to quality function deployment planning with financial consideration. Computers & Operations Research, 29(11), 1447–1463.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
别名	Bayesian QFD, Probabilistic QFD, Bayesian House of Quality, Bayesian Voice of the Customer Analysis	DOE, experimental design, factorial experimentation, planned experimentation
相关	5	3
摘要	Bayesian Quality Function Deployment (Bayesian QFD) integrates Bayesian probabilistic inference into the classical House of Quality framework to handle uncertainty in customer preference data and relationship matrices. By expressing relationship weights and importance ratings as probability distributions rather than point estimates, it propagates uncertainty through the planning process and yields more defensible engineering prioritization decisions under incomplete or conflicting customer information.	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.