A grey-ANN approach for optimizing the QFN component assembly process for smart phone application. Issue 2 (4th April 2016) - Huang, Chien-Yi; Chen, Ching-Hsiang; Lin, Yueh-Hsun
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.