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International Journal of Production Research Volume 34, 1996 - Issue 6
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Original Articles

Multivariate statistical process control for autocorrelated processes

G. C. RUNGER Dept. of Management Science and Statistics, University of Maryland, College Park, MD, 20742, USA
Pages 1715-1724 | Received 01 Dec 1994, Published online: 19 Apr 2007

Citations (18)

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Read on this site (8)

Binhui Wang, Zhifeng He & Lianjie Shu. (2023) A generalized exponentially weighted moving average control chart for monitoring autocorrelated vectors. Communications in Statistics - Simulation and Computation 52:6, pages 2559-2577.
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Yiqi Liu, Yumin Liu & Uk Jung. (2020) Nonparametric multivariate control chart based on density-sensitive novelty weight for non-normal processes. Quality Technology & Quantitative Management 17:2, pages 203-215.
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Canan Bilen, Anakaorn Khan & Wichai Chattinnawat. (2017) Dual-monitoring scheme for multivariate autocorrelated cascade processes with EWMA and MEWMA charts. Quality Technology & Quantitative Management 14:2, pages 156-177.
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S. Siripanthana & E. C. Stillman. (2016) Sufficient reduction methods for multivariate time-dependent health surveillance data. Communications in Statistics - Theory and Methods 45:4, pages 950-966.
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Ji Hoon Kang & Seoung Bum Kim. (2013) A clustering algorithm-based control chart for inhomogeneously distributed TFT-LCD processes. International Journal of Production Research 51:18, pages 5644-5657.
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A. Snoussi. (2011) SPC for short-run multivariate autocorrelated processes. Journal of Applied Statistics 38:10, pages 2303-2312.
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A. Das, J. Maiti & R.N. Banerjee. (2010) A hierarchical process monitoring strategy for a serial multi-stage manufacturing system. International Journal of Production Research 48:8, pages 2459-2479.
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George C. Runger. (2002) Assignable Causes and Autocorrelation: Control Charts for Observations or Residuals?. Journal of Quality Technology 34:2, pages 165-170.
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Articles from other publishers (10)

Muhammad Mashuri, Muhammad Ahsan, Muhammad Hisyam Lee, Dedy Dwi Prastyo & Wibawati. (2021) PCA-based Hotelling's T2 chart with fast minimum covariance determinant (FMCD) estimator and kernel density estimation (KDE) for network intrusion detection. Computers & Industrial Engineering 158, pages 107447.
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Ji Hoon Kang, Jaehong Yu & Seoung Bum Kim. (2016) Adaptive nonparametric control chart for time-varying and multimodal processes. Journal of Process Control 37, pages 34-45.
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Ji Hoon Kang & Seoung Bum Kim. (2015) False alarm classification for multivariate manufacturing processes of thin film transistor–liquid crystal displays. Journal of Process Control 35, pages 21-29.
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Yuan Yao & Furong Gao. 2013. Computer Modeling for Injection Molding. Computer Modeling for Injection Molding 355 375 .
S. Bersimis, S. Psarakis & J. Panaretos. (2006) Multivariate statistical process control charts: an overview. Quality and Reliability Engineering International 23:5, pages 517-543.
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Olha Bodnar & Wolfgang Schmid. 2006. Frontiers in Statistical Quality Control 8. Frontiers in Statistical Quality Control 8 55 73 .
S. Lane, E. B. MartinA. J. Morris & P. Gower. (2016) Application of exponentially weighted principal component analysis for the monitoring of a polymer film manufacturing process. Transactions of the Institute of Measurement and Control 25:1, pages 17-35.
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Elvira N. Loredo, Duangporn Jearkpaporn & Connie M. Borror. (2002) Model‐based control chart for autoregressive and correlated data. Quality and Reliability Engineering International 18:6, pages 489-496.
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. (2002) Monitoring process manufacturing performance. IEEE Control Systems 22:5, pages 26-39.
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Christina M. Mastrangelo, Joseph M. Porter & Robert V. BaxleyJr.Jr.. 2001. Frontiers in Statistical Quality Control 6. Frontiers in Statistical Quality Control 6 228 246 .

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