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最適化支援品質機能展開(Optimization-Assisted Quality Function Deployment)×応答曲面法 (RSM)×
分野実験計画法実験計画法
系統Process / pipelineHypothesis test
提唱年1990s–2000s (QFD base: ~1966)1951
提唱者Yoji Akao (QFD); optimization extensions by various researchers (1990s–2000s)George E. P. Box & K. B. Wilson
種類Integrated engineering design methodSecond-order polynomial response surface model
原典Akao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press, Cambridge, MA. ISBN: 978-0915299416Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45. link ↗
別名Optimization-integrated QFD, QFD with optimization, Mathematical programming QFD, OA-QFDRSM, Central Composite Design, Box-Behnken Design, CCD
関連47
概要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.Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics.
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ScholarGate手法を比較: Optimization-assisted quality function deployment · Response Surface Methodology. 2026-06-15に以下より取得 https://scholargate.app/ja/compare