A grey-ANN approach for optimizing the QFN component assembly process for smart phone application
Abstract
Purpose
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.
Design/methodology/approach
The innovative hybrid algorithm gray relational analysis (GRA)-ANN and the GRA-Entropy are proposed to effectively solve the multi-response optimization problem.
Findings
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.
Originality/value
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.
Keywords
Citation
Huang, C.-Y., Chen, C.-H. and Lin, Y.-H. (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-10-2015-0034
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited