Process / pipelineEngineering methods

Hybrid Taguchi Method — Integrated Taguchi Optimization

The Hybrid Taguchi Method combines Taguchi's orthogonal array experimental design and signal-to-noise ratio analysis with a secondary optimization or analysis technique — such as grey relational analysis, response surface methodology, artificial neural networks, or fuzzy logic — to handle multiple response variables or complex nonlinear relationships that classical Taguchi alone cannot resolve efficiently. It is widely used in manufacturing, materials engineering, and process optimization.

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Sources

  1. Taguchi, G. (1987). System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Costs. UNIPUB/Kraus International Publications. ISBN: 978-0527916213
  2. Lin, C. L. (2004). Use of the Taguchi method and grey relational analysis to optimize turning operations with multiple performance characteristics. Materials and Manufacturing Processes, 19(2), 209–220. DOI: 10.1081/AMP-120029852

Related methods

ScholarGateHybrid Taguchi Method (Hybrid Taguchi Optimization Method). Retrieved 2026-06-04 from https://scholargate.app/en/experimental-design/hybrid-taguchi-method