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仿真辅助质量功能展开×基于仿真的实验设计×
领域实验设计实验设计
方法族Process / pipelineProcess / pipeline
起源年份1990s–2000s (QFD: 1966; simulation integration: ~1995–2005)1970s–1990s (formalized with computer experimentation growth)
提出者Yoji Akao (QFD foundation); simulation integration developed by engineering researchers in 1990s–2000sMultiple contributors; systematized by Jack P.C. Kleijnen and Thomas J. Santner et al.
类型Hybrid engineering design and quality planning methodHybrid experimental-computational method
开创性文献Akao, Y. (Ed.). (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press. ISBN: 978-0915299416Santner, T. J., Williams, B. J., & Notz, W. I. (2003). The Design and Analysis of Computer Experiments. Springer. ISBN: 978-0387954202
别名SA-QFD, simulation-integrated QFD, simulation-driven house of quality, QFD with simulationSimulation-based DoE, Virtual DoE, Computer-aided DoE, SA-DoE
相关65
摘要Simulation-assisted quality function deployment (SA-QFD) integrates computational simulation into the classic QFD framework to replace or supplement costly physical prototypes when evaluating how engineering design decisions satisfy customer requirements. By embedding simulation models — such as finite element analysis, discrete-event simulation, or system dynamics — within the House of Quality matrix, engineers can rapidly quantify the impact of technical characteristics on customer satisfaction and iteratively refine design priorities before committing to production.Simulation-assisted design of experiments (SA-DoE) integrates computational simulation tools — such as finite element analysis (FEA), computational fluid dynamics (CFD), or discrete-event simulation — with classical DoE principles to systematically explore the factor space of a system. Rather than running costly or hazardous physical trials, researchers execute a structured set of virtual experiments across selected factor combinations, then fit a surrogate model to the simulation outputs to understand main effects, interactions, and optimal settings.
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  3. PUBLISHED

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ScholarGate方法对比: Simulation-assisted quality function deployment · Simulation-assisted design of experiments. 于 2026-06-17 检索自 https://scholargate.app/zh/compare