Research on the Production Scheduling Method of a Semiconductor Packaging Test Based With the Clustering Method
Zhonghua Han,
Quan Zhang,
Yongqing Jiang and
Bin Duan
Additional contact information
Zhonghua Han: Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China & Department of Digital Faculty, Shenyang Institute of Automation, Chinese Academy of Sciences, Beijing, China
Quan Zhang: Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China
Yongqing Jiang: Chongqing University, Chongqing, China
Bin Duan: Shenyang Institute of Automation, Chinese Academy of Sciences, Beijing, China
International Journal of Information Systems and Supply Chain Management (IJISSCM), 2019, vol. 12, issue 2, 36-56
Abstract:
In this article, the scheduling of modern industrial production is studied. The research on scheduling of semiconductor packaging and testing is put forward. A new solution of packaging and test scheduling based on dynamic optimization is proposed. The decomposition strategy is used to solve the problem of the encapsulation test scheduling problem. The complexity of the problem is reduced to ensure the consistency of optimization. In the method, an AP clustering algorithm is used to optimize the matching relationship between job and resource. The neural network method is used to solve the problem. The research of this project will fully combine the characteristics of packaging and testing production. In view of the existing production scheduling theory, there is a big gap to a semiconductor packaging and testing enterprises for the actual research background. This simulation experiments show that the method can be used on packaged production scheduling to provide a viable, effective method support.
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 8/IJISSCM.2019040103 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jisscm:v:12:y:2019:i:2:p:36-56
Access Statistics for this article
International Journal of Information Systems and Supply Chain Management (IJISSCM) is currently edited by John Wang
More articles in International Journal of Information Systems and Supply Chain Management (IJISSCM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().