This paper aims to propose an innovative parametric design for artificial neural network (ANN) modeling for the multi-quality function problem to determine the optimal process scenarios.
The innovative hybrid algorithm gray relational analysis (GRA)-ANN and the GRA-Entropy are proposed to effectively solve the multi-response optimization problem.
Both the GRA-ANN and the GRA-Entropy analytical approaches find that the optimal process scenario is a stencil aperture of 57 per cent and immediate processing of the printed circuit board after exposure to a room environment.
A six-week confirmation test indicates that the optimal process has improved quad flat non-lead assembly yield from 99.12 to 99.78 per cent.
Huang, C., Chen, C. and Lin, Y. (2016), "A grey-ANN approach for optimizing the QFN component assembly process for smart phone application", Soldering & Surface Mount Technology, Vol. 28 No. 2, pp. 63-73. https://doi.org/10.1108/SSMT-10-2015-0034Download as .RIS
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