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检索条件"主题词=Multivariate Statistical Process Control"
261 条 记 录,以下是91-100 订阅
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Monitoring multivariate process variability via eigenvalues
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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 113卷 269-281页
作者: Fan, Jinyu Shu, Lianjie Zhao, Honghao Yeung, Hangfai Univ Macau Fac Business Adm Zhuhai Guangdong Peoples R China Macau Univ Sci & Technol Sch Business Macau Peoples R China
Various methods have been proposed to monitor changes in a process covariance matrix. In view that a covariance matrix can be fully defined by its eigenvalues and eigenvectors, this paper suggests monitoring the covar... 详细信息
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controlling Bivariate Categorical processes using Scan Rules
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METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY 2017年 第4期19卷 1135-1149页
作者: Bersimis, Sotirios Sachlas, Athanasios Castagliola, Philippe Univ Piraeus Dept Stat & Insurance Sci 80 Karaoli & Dimitriou Str Piraeus 18534 Greece Univ Nantes LUNAM Univ 2 Ave Prof Jean RouxelBP 539 F-44475 Carquefou France CNRS UMR 6597 IRCCyN 2 Ave Prof Jean RouxelBP 539 F-44475 Carquefou France
In this paper, we introduce a methodology for efficiently monitoring a health process that classify the intervention outcome, in two dependent characteristics, as "absolutely successful", "with minor bu... 详细信息
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ARL Numerics for MEWMA Charts
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JOURNAL OF QUALITY TECHNOLOGY 2017年 第1期49卷 78-89页
作者: Knoth, Sven Helmut Schmidt Univ Univ Fed Armed Forces Hamburg Dept Math & Stat POB 700822 D-22008 Hamburg Germany
The FORTRAN code in Bodden and Rigdon (1999) for the in-control average run length (ARL) of multivariate exponentially weighted moving average charts (MEWMA) became quite popular and is widely used in statistical soft... 详细信息
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On reducing false alarms in multivariate statistical process control
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CHEMICAL ENGINEERING RESEARCH & DESIGN 2010年 第4A期88卷 430-436页
作者: Chen, Tao Nanyang Technol Univ Sch Chem & Biomed Engn Singapore 637459 Singapore
The primary objective of this note is to reduce the false alarms in multivariate statistical process control (MSPC). The issue of false alarms is inherent within MSPC as a result of the definition of control limits. I... 详细信息
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An effective multivariate control chart for detecting small mean shifts using support vector data description
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ADVANCES IN MECHANICAL ENGINEERING 2018年 第11期10卷
作者: Xia, Beixin Jian, Zheng Liu, Lei Li, Long Shanghai Univ Sch Management Shanghai Peoples R China Shanghai Univ Sch Mechatron Engn & Automat 149 Yanchang Rd Shanghai 200072 Peoples R China Apple Inc Cupertino CA USA
Conventional multivariate cumulative sum control charts are more sensitive to small shifts than T2 control charts, but they cannot get the knowledge of manufacturing process through the learning of in-control data due... 详细信息
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An extension to RPCA parameter selection and process monitoring
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IFAC-PapersOnLine 2017年 第1期50卷 14764-14769页
作者: Rehmer, Alexander Kroll, Andreas Department of Measurement and Control Institute for System Analytics and Control Faculty of Mechanical Engineering University of Kassel Kassel Germany
multivariate statistical process control (MSPC) techniques such as Principal Component Analysis (PCA) and Partial Least Squares (PLS) have found wide application especially in the statistical modeling and monitoring o... 详细信息
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Fault detection in the Tennessee Eastman benchmark process with nonlinear singular spectrum analysis
Fault detection in the Tennessee Eastman benchmark process w...
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20th World Congress of the International-Federation-of-Automatic-control (IFAC)
作者: Krishnannair, S. Aldrich, C. Univ Zululand ZA-3886 Kwa Dlangezwa South Africa Univ Stellenbosch Dept Proc Engn Private Bag XI ZA-7602 Matieland South Africa Curtin Univ Western Australia Sch Mines Dept Min Engn & Met Engn GPO Box U1987 Perth WA 6845 Australia
multivariate statistical process monitoring methods aim at detecting and identifying faults in the performance of processes over time in order to keep the process under control. Singular spectrum analysis (SSA) is a p... 详细信息
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Structural Damage Fault Detection Using Artificial Neural Network Profile Monitoring  7
Structural Damage Fault Detection Using Artificial Neural Ne...
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7th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO)
作者: Awad, Mahmoud AlHamaydeh, Mohammad Mohamed, Ahmed Fares Amer Univ Sharjah Dept Ind Engn Sharjah U Arab Emirates Amer Univ Sharjah Dept Civil Engn Sharjah U Arab Emirates
In today's world, structural development with reliability and integrity is an ever demanding process. Fault detection is the identification of normal healthy behavior of a system or process and recognition of any ... 详细信息
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Fault detection in the Tennessee Eastman benchmark process with nonlinear singular spectrum analysis
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IFAC-PapersOnLine 2017年 第1期50卷 8005-8010页
作者: Krishnannair S. Aldrich C. University of Zululand Kwadlangezwa3886 South Africa Department of Process Engineering University of Stellenbosch Private Bag XI Matieland 7602 South Africa Department of Mining Engineering and Metallurgical Engineering Western Australian School of Mines Curtin University GPO Box U1987WA 6845 Australia
multivariate statistical process monitoring methods aim at detecting and identifying faults in the performance of processes over time in order to keep the process under control. Singular spectrum analysis (SSA) is a p... 详细信息
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Variable Selection for multivariate statistical process control
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JOURNAL OF QUALITY TECHNOLOGY 2010年 第3期42卷 242-259页
作者: Gonzalez, Isabel Sanchez, Ismael Univ Carlos III Madrid Dept Mech Engn Madrid 28911 Spain Univ Carlos III Madrid Dept Stat Madrid 28911 Spain
This article proposes a methodology to select a subset of variables to measure and monitor for multivariate statistical process control (SPC). In contrast with most dimensionality reduction approaches for SPC, we redu... 详细信息
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