Multi-response full factorial design
Multi-response full factorial design extends the classic full factorial experiment by measuring and jointly optimizing two or more response variables at the same time. Every combination of all factor levels is tested, providing complete main-effect and interaction information for each response. A desirability function or Pareto-front approach then reconciles competing responses into a single optimal factor setting, making this the method of choice when engineering or process goals involve trade-offs among several quality characteristics simultaneously.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. · ISBN 978-1119492443
- Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. · DOI 10.1080/00224065.1980.11980968
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Related methods
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