A Neural Networks Approach Combined with Taguchi's Method for IC Leadframe Dam-bar Shearing Process

CCUR > College of Natural Science and Engineering > College of Engineering > Department of Mechanical Engineering > journal articles > Item 987654321/2495

Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/2495

Title:	A Neural Networks Approach Combined with Taguchi's Method for IC Leadframe Dam-bar Shearing Process
Authors:	Lin, Z. C. Chang, D. Y.
Contributors:	機械系
Keywords:	Neural networks Taguchi's method Metal shearing
Date:	2008
Issue Date:	2009-11-03 09:17:08 (UTC+8)
Abstract:	In Taguchi method, a preferred factor solution can be derived by factional factor experiments and factor level response analysis. However, the experimental error caused by factor levels orthogonality in orthogonal arrays is inevitable. In order to improve this, a network approach combines with Taguchi's method by progressive training is proposed, which integrates the experimental orthogonality and the learning ability of neural network to establish an inferring network model. Two cases of IC leadframe dam-bar shearing have carried out to demonstrate the modeling process. By increasing a few additional experiments, an optimal factor level combination can be inferred, which is more objective and accurate than the traditional Taguchi's method does.
Relation:	JOURNAL OF THE CHINESE SOCIETY OF MECHANICAL ENGINEERS Volume: 29 Issue: 5 Pages: 355-364
Appears in Collections:	[Department of Mechanical Engineering ] journal articles

Files in This Item:

There are no files associated with this item.