A grey-ANN approach for optimizing the QFN component assembly process for smart phone application

التفاصيل البيبلوغرافية
العنوان: A grey-ANN approach for optimizing the QFN component assembly process for smart phone application
المؤلفون: Chien-Yi Huang, Ching-Hsiang Chen, Yueh-Hsun Lin
المصدر: Soldering & Surface Mount Technology. 28:63-73
بيانات النشر: Emerald, 2016.
سنة النشر: 2016
مصطلحات موضوعية: 0209 industrial biotechnology, Engineering, Optimization problem, Artificial neural network, business.industry, Design of experiments, 02 engineering and technology, Condensed Matter Physics, Hybrid algorithm, Grey relational analysis, Stencil, Parametric design, 020901 industrial engineering & automation, Computer engineering, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, General Materials Science, Quad Flat No-leads package, Electrical and Electronic Engineering, business, Simulation
الوصف: 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.
تدمد: 0954-0911
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2dbfd498c16e191eb26fe4cc3443589f
https://doi.org/10.1108/ssmt-10-2015-0034
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........2dbfd498c16e191eb26fe4cc3443589f
قاعدة البيانات: OpenAIRE