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Parameter optimization of a multi-response process for lead frame manufacturing by employing artificial neural networks

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Abstract

This study proposes an effective means of applying a neural network approach to parameter optimization for a multi-response problem. No matter what type of experimental designs are being employed, the proposed approach can be directly applied. In addition, the design factors with level settings or with continuous values can be also solved with the proposed approach. Not only can parameter optimization be achieved, but the effects of the control factors reacting on a multi-response system can also be simultaneously determined. An illustrative example given courtesy of a lead frame manufacturer in Taiwan is employed to demonstrate the effectiveness of the proposed approach .

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Authors and Affiliations

  1. Department of Information Management and Research Group in Systematic and Theoretical Sciences, National Taitung University, 684, Sec. 1, Chung Hua Rd., Taitung, Taiwan, 950

    Kun-Lin Hsieh

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  1. Kun-Lin Hsieh
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Correspondence to Kun-Lin Hsieh.

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Hsieh, KL. Parameter optimization of a multi-response process for lead frame manufacturing by employing artificial neural networks. Int J Adv Manuf Technol 28, 584–591 (2006). https://doi.org/10.1007/s00170-004-2383-1

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  • DOI: https://doi.org/10.1007/s00170-004-2383-1

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