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

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 .