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Penyebaran Kualiti Bayesian (Bayesian Quality Function Deployment)×Reka Bentuk Eksperimen×
BidangReka Bentuk EksperimenReka Bentuk Eksperimen
KeluargaProcess / pipelineProcess / pipeline
Tahun asalQFD: 1966–1972; Bayesian QFD extensions: 2000s–present1935
PengasasYoji Akao (QFD); Bayesian extension developed by multiple researchers including Fung, Tang, and colleaguesRonald A. Fisher
JenisProbabilistic customer-driven design planning methodExperimental planning framework
Sumber perintisTang, 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. DOI ↗Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
AliasBayesian QFD, Probabilistic QFD, Bayesian House of Quality, Bayesian Voice of the Customer AnalysisDOE, experimental design, factorial experimentation, planned experimentation
Berkaitan53
RingkasanBayesian 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.
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ScholarGateBandingkan kaedah: Bayesian Quality Function Deployment · Design of experiments. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare