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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yu-ming Liu Jun Liang Ji-xin Qian |
| Copyright Year | 2004 |
| Description | Author affiliation: Nat. Lab of Ind. Control Technol., Zhejiang Univ., Hangzhou, China (Yu-ming Liu; Jun Liang; Ji-xin Qian) |
| Abstract | A method for constructing moving blocks bootstrap control chart for dependent multivariate data was proposed. In this method the statistics of the control charts were firstly obtained by principal component analysis, then a modified MBB was used to determine their control limits which can not be based on independent and identically distributed (IID) assumption. Empirical average run length and false alarm rate were proposed to evaluate the control charts. Two examples, adopting simulation data and real industrial data respectively, were given to illustrate the method, in which some results about factors' impact on MBB, such as sample size , moving block size, block number, et al., were obtained. The results show MBB-based method is superior to PCA-based method under certain conditions and is an available way to establish control charts for weakly dependent multivariate data. |
| Starting Page | 5177 |
| Ending Page | 5182 |
| File Size | 350800 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780385667 |
| ISSN | 1062922X |
| DOI | 10.1109/ICSMC.2004.1401016 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-10-10 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Control charts Industrial control Statistical analysis Principal component analysis Statistical distributions Sampling methods Parametric statistics Weight control Size control Distributed computing |
| Content Type | Text |
| Resource Type | Article |
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