Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production
Joint Authors
Lv, Shengping
Zheng, Binbin
Kim, Hoyeol
Yue, Qiangsheng
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-01
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Information Technology and Computer Science
Abstract EN
Improving the accuracy of material feeding for printed circuit board (PCB) template orders can reduce the overall cost for factories.
In this paper, a data mining approach based on multivariate boxplot, multiple structural change model (MSCM), neighborhood component feature selection (NCFS), and artificial neural networks (ANN) was developed for the prediction of scrap rate and material feeding optimization.
Scrap rate related variables were specified and 30,117 samples of the orders were exported from a PCB template production company.
Multivariate boxplot was developed for outlier detection.
MSCM was employed to explore the structural change of the samples that were finally partitioned into six groups.
NCFS and ANN were utilized to select scrap rate related features and construct prediction models for each group of the samples, respectively.
Performances of the proposed model were compared to manual feeding, ANN, and the results indicate that the approach exhibits obvious superiority to the other two methods by reducing surplus rate and supplemental feeding rate simultaneously and thereby reduces the comprehensive cost of raw material, production, logistics, inventory, disposal, and delivery tardiness compensation.
American Psychological Association (APA)
Lv, Shengping& Zheng, Binbin& Kim, Hoyeol& Yue, Qiangsheng. 2018. Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1184374
Modern Language Association (MLA)
Lv, Shengping…[et al.]. Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1184374
American Medical Association (AMA)
Lv, Shengping& Zheng, Binbin& Kim, Hoyeol& Yue, Qiangsheng. Data Mining for Material Feeding Optimization of Printed Circuit Board Template Production. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1184374
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184374