CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization
Gu, Nong1; Cao, Zhiqiang2; Xie, Liangjun3; Creighton, Douglas1; Tan, Min2; Nahavandi, Saeid1
Source PublicationJOURNAL OF INTELLIGENT MANUFACTURING
2013-12-01
Volume24Issue:6Pages:1241-1252
SubtypeArticle
AbstractIdentification of unnatural control chart patterns (CCPs) from manufacturing process measurements is a critical task in quality control as these patterns indicate that the manufacturing process is out-of-control. Recently, there have been numerous efforts in developing pattern recognition and classification methods based on artificial neural network to automatically recognize unnatural patterns. Most of them assume that a single type of unnatural pattern exists in process data. Due to this restrictive assumption, severe performance degradations are observed in these methods when unnatural concurrent CCPs present in process data. To address this problem, this paper proposes a novel approach based on singular spectrum analysis (SSA) and learning vector quantization network to identify concurrent CCPs. The main advantage of the proposed method is that it can be applied to the identification of concurrent CCPs in univariate manufacturing processes. Moreover, there are no permutation and scaling ambiguities in the CCPs recovered by the SSA. These desirable features make the proposed algorithm an attractive alternative for the identification of concurrent CCPs. Computer simulations and a real application for aluminium smelting processes confirm the superior performance of proposed algorithm for sets of typical concurrent CCPs.
KeywordControl Charts Concurrent Patterns Singular Spectrum Analysis Learning Vector Quantization Networks Aluminium Smelting
WOS HeadingsScience & Technology ; Technology
WOS KeywordINDEPENDENT COMPONENT ANALYSIS ; NEURAL-NETWORK APPROACH ; BLIND-EQUALIZATION ; RECOGNITION ; CRITERION ; PARAMETERS ; ALGORITHM ; SYSTEM
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Manufacturing
WOS IDWOS:000326297800014
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3503
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Deakin Univ, Ctr Intelligent Syst Res, Waurn Ponds, Vic 3216, Australia
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Schlumberger Ltd, Houston, TX 77073 USA
Recommended Citation
GB/T 7714
Gu, Nong,Cao, Zhiqiang,Xie, Liangjun,et al. Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization[J]. JOURNAL OF INTELLIGENT MANUFACTURING,2013,24(6):1241-1252.
APA Gu, Nong,Cao, Zhiqiang,Xie, Liangjun,Creighton, Douglas,Tan, Min,&Nahavandi, Saeid.(2013).Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization.JOURNAL OF INTELLIGENT MANUFACTURING,24(6),1241-1252.
MLA Gu, Nong,et al."Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization".JOURNAL OF INTELLIGENT MANUFACTURING 24.6(2013):1241-1252.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Gu, Nong]'s Articles
[Cao, Zhiqiang]'s Articles
[Xie, Liangjun]'s Articles
Baidu academic
Similar articles in Baidu academic
[Gu, Nong]'s Articles
[Cao, Zhiqiang]'s Articles
[Xie, Liangjun]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Gu, Nong]'s Articles
[Cao, Zhiqiang]'s Articles
[Xie, Liangjun]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.