Hybrid Fractional Factorial Design
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.
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 978-1119113478
- Wu, C. F. J., & Hamada, M. S. (2000). Experiments: Planning, Analysis, and Parameter Design Optimization. Wiley. · ISBN 978-0471255116
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Related methods
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