A grey-ANN approach for optimizing the QFN component assembly process for smart phone application. Issue 2 (4th April 2016)
- Record Type:
- Journal Article
- Title:
- A grey-ANN approach for optimizing the QFN component assembly process for smart phone application. Issue 2 (4th April 2016)
- Main Title:
- A grey-ANN approach for optimizing the QFN component assembly process for smart phone application
- Authors:
- Huang, Chien-Yi
Chen, Ching-Hsiang
Lin, Yueh-Hsun - Abstract:
- 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.
- Is Part Of:
- Soldering & surface mount technology. Volume 28:Issue 2(2016)
- Journal:
- Soldering & surface mount technology
- Issue:
- Volume 28:Issue 2(2016)
- Issue Display:
- Volume 28, Issue 2 (2016)
- Year:
- 2016
- Volume:
- 28
- Issue:
- 2
- Issue Sort Value:
- 2016-0028-0002-0000
- Page Start:
- 63
- Page End:
- 73
- Publication Date:
- 2016-04-04
- Subjects:
- Grey relational analysis -- Design of experiment -- Multi-response process -- QFN component
Brazing -- Periodicals
Solder and soldering -- Periodicals
671.5605 - Journal URLs:
- http://www.emeraldinsight.com/journals.htm?issn=0954-0911 ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/SSMT-10-2015-0034 ↗
- Languages:
- English
- ISSNs:
- 0954-0911
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8327.242650
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8216.xml