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多响应分数析因设计×多响应响应面法×
领域实验设计实验设计
方法族Process / pipelineProcess / pipeline
起源年份1961 (fractional factorial foundation); 1980 (multi-response desirability approach)1980 (Derringer & Suich desirability function); RSM roots ~1951 (Box & Wilson)
提出者George E.P. Box, J. Stuart Hunter, and William G. Hunter (fractional factorial basis); Derringer & Suich (multi-response desirability extension)Derringer & Suich (desirability function approach); Myers & Montgomery (RSM framework)
类型Experimental design with simultaneous multi-response optimizationExperimental optimization technique
开创性文献Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗
别名MRFFD, multi-response FFD, multi-objective fractional factorial design, simultaneous multi-response fractional factorialMulti-response RSM, MRSM, Multi-objective RSM, Multiple response optimization
相关46
摘要Multi-response fractional factorial design (MRFFD) applies a resolution-efficient fractional factorial experiment to study multiple response variables simultaneously. By running only a carefully chosen fraction of the full factorial treatment combinations, the experimenter gathers enough information to fit individual response models for each output and then optimize all responses jointly — typically via a composite desirability function — while keeping the number of experimental runs tractable.Multi-response Response Surface Methodology (MRSM) extends classical RSM to situations where an experiment generates two or more response variables that must be optimized simultaneously. Rather than tuning factor settings for a single output, MRSM fits a separate second-order polynomial model for each response, then combines them — most commonly via Derringer and Suich's desirability function — to find factor settings that satisfy all objectives at once.
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ScholarGate方法对比: Multi-response Fractional Factorial Design · Multi-response Response Surface Methodology. 于 2026-06-19 检索自 https://scholargate.app/zh/compare