This study presents an effective means of applying neural networks to achieve robust design with dynamic characteristic considerations. Two neural networks are constructed to train the data set in the Taguchi’s orthogonal array (OA): one to search for the optimal condition, and the other to forecast the system’s response value. A measuring system employed in semiconductor manufacturing demonstrates the proposed approach’s effectiveness. According to those results, the proposed approach outperforms the conventional Taguchi method. By using the proposed approach, the adjustment factors are not a prerequisite for the dynamic characteristic problem. Moreover, the proposed approach enhances the generalization capability.
Su, C. and Hsieh, K. (1998), "Applying neural network approach to achieve robust design for dynamic quality characteristics", International Journal of Quality & Reliability Management, Vol. 15 No. 5, pp. 509-519. https://doi.org/10.1108/02656719810196243Download as .RIS
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