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ハイブリッド分割要因計画×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1970s–1990s (formalized as a distinct design class)1951
提唱者Developed across the DOE community; foundational contributions by Box, Hunter & Hunter and Wu & HamadaGeorge E. P. Box & K. B. Wilson
種類Experimental designSecond-order polynomial response surface model
原典Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478Box, 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HFFD, hybrid FFD, combined fractional factorial design, mixed fractional factorial designRSM, Central Composite Design, Box-Behnken Design, CCD
関連37
概要A hybrid fractional factorial design (HFFD) merges two or more fractional factorial sub-designs — often involving factors at different numbers of levels or with different aliasing structures — into a single coordinated experiment. The goal is to achieve estimation capabilities (main effects, targeted two-factor interactions) that no single standard fractional design can provide within the same run count, making it especially valuable in engineering development and industrial process optimization.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: Hybrid Fractional Factorial Design · Response Surface Methodology. 2026-06-19に以下より取得 https://scholargate.app/ja/compare