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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 36, 2004 - Issue 4
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Articles

Multivariate Control Charts for Monitoring Autocorrelated Processes

Pages 367-379 | Published online: 16 Feb 2018

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Read on this site (14)

Jian Li, Qiang Zhou & Dong Ding. (2020) Efficient monitoring of autocorrelated Poisson counts. IISE Transactions 52:7, pages 769-779.
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Jian Li, Jiakun Xu & Qiang Zhou. (2018) Monitoring serially dependent categorical processes with ordinal information. IISE Transactions 50:7, pages 596-605.
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Jian Li & Qiang Zhou. (2017) A General Approach for Monitoring Serially Dependent Categorical Processes. Journal of Quality Technology 49:4, pages 365-379.
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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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Erdi Dasdemir, Christian Weiß, Murat Caner Testik & Sven Knoth. (2016) Evaluation of Phase I analysis scenarios on Phase II performance of control charts for autocorrelated observations. Quality Engineering 28:3, pages 293-304.
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Yanfen Shang, Fugee Tsung & Changliang Zou. (2013) Statistical process control for multistage processes with binary outputs. IIE Transactions 45:9, pages 1008-1023.
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Manuel Vargas, José Luis Alfaro & José Mondéjar. (2009) On the Run Length of a State-Space Control Chart for Multivariate Autocorrelated Data. Communications in Statistics - Simulation and Computation 38:9, pages 1823-1833.
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Zhang Wu, Jianxin Jiao & Zhen He. (2009) A control scheme for monitoring the frequency and magnitude of an event. International Journal of Production Research 47:11, pages 2887-2902.
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Changliang Zou & Fugee Tsung. (2008) Directional MEWMA Schemes for Multistage Process Monitoring and Diagnosis. Journal of Quality Technology 40:4, pages 407-427.
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Lianjie Shu, Wei Jiang & Kwok-Leung Tsui. (2008) A Weighted CUSUM Chart for Detecting Patterned Mean Shifts. Journal of Quality Technology 40:2, pages 194-213.
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Kaibo Wang & Fugee Tsung. (2008) An Adaptive T2 Chart for Monitoring Dynamic Systems. Journal of Quality Technology 40:1, pages 109-123.
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Shing I. Chang & Kui Zhang. (2007) Statistical Process Control for Variance Shift Detections of Multivariate Autocorrelated Processes. Quality Technology & Quantitative Management 4:3, pages 413-435.
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Wei Jiang, Terrence E. Murphy, Kwok-Leung Tsui & Yang Zhao. 2023. Springer Handbook of Engineering Statistics. Springer Handbook of Engineering Statistics 199 220 .
J P Rojas Suárez, J Gónzalez Mendoza & M Vergel Ortega. (2020) Control panels in human talent processes for professionals in physics in public organizations. Journal of Physics: Conference Series 1645:1, pages 012019.
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Wei Fan, Qiang Zhou, Jian Li & Zhongkui Zhu. (2018) A Wavelet-Based Statistical Approach for Monitoring and Diagnosis of Compound Faults With Application to Rolling Bearings. IEEE Transactions on Automation Science and Engineering 15:4, pages 1563-1572.
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Fangyi He, Tiantian Mao, Taizhong Hu & Lianjie Shu. (2018) A new type of change-detection scheme based on the window-limited weighted likelihood ratios. Expert Systems with Applications 94, pages 149-163.
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Dong Ding, Dongdong Xiang & Jian Li. (2017) Directional monitoring of categorical processes with serial dependence. Computers & Industrial Engineering 113, pages 502-511.
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Camil Fuchs & Ron S. Kenett. 2014. Wiley StatsRef: Statistics Reference Online. Wiley StatsRef: Statistics Reference Online.
José Luis Alfaro Navarro, Manuel Vargas Vargas, María Encarnación Andrés Martínez & José Mondéjar Jiménez. (2014) A new proposal to solve the autocorrelation problem for monitoring processes in the cutlery industry. Japan Journal of Industrial and Applied Mathematics 31:2, pages 323-333.
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Xuan Huang, Søren Bisgaard & Nuo Xu. (2014) Model-based Multivariate Monitoring Charts for Autocorrelated Processes. Quality and Reliability Engineering International 30:4, pages 527-543.
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Ming Jie Yang & Xue Min Zi. (2014) The Comparison among Three Control Charts for Monitoring the Auto Correlated Processes. Applied Mechanics and Materials 490-491, pages 1579-1583.
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Adedeji BadiruWei Jiang & John Farr. 2013. Handbook of Industrial and Systems Engineering, Second Edition. Handbook of Industrial and Systems Engineering, Second Edition 933 954 .
Wen Wan Yang, Xue Min Zi & Chang Liang Zou. (2012) A Directional Multivariate Control Chart for Monitoring Univariate Autocorrelated Processes. Applied Mechanics and Materials 217-219, pages 2607-2613.
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Florbela Correia, Rui Nêveda & Pedro Oliveira. (2011) Chronic respiratory patient control by multivariate charts. International Journal of Health Care Quality Assurance 24:8, pages 621-643.
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Thomas P. Ryan. 2011. Statistical Methods for Quality Improvement. Statistical Methods for Quality Improvement 353 384 .
Siu-Tong Au, Rong Duan, Siamak G. Hesar & Wei Jiang. (2008) A framework of irregularity enlightenment for data pre-processing in data mining. Annals of Operations Research 174:1, pages 47-66.
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Fujee Tsung & Kaibo Wang. 2010. Frontiers in Statistical Quality Control 9. Frontiers in Statistical Quality Control 9 19 35 .
Kaibo Wang & Fugee Tsung. (2008) An adaptive dimension reduction scheme for monitoring feedback‐controlled processes. Quality and Reliability Engineering International 25:3, pages 283-298.
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Camil Fuchs & Ron S. Kenett. 2007. Encyclopedia of Statistics in Quality and Reliability. Encyclopedia of Statistics in Quality and Reliability.
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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K. Triantafyllopoulos. (2006) Multivariate Control Charts Based on Bayesian State Space Models. Quality and Reliability Engineering International 22:6, pages 693-707.
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Wei Jiang, Terrence Murphy & Kwok-Leung Tsui. 2006. Springer Handbook of Engineering Statistics. Springer Handbook of Engineering Statistics 173 192 .
John Farr & Wei Jiang. 2005. Handbook of Industrial and Systems Engineering. Handbook of Industrial and Systems Engineering 3-1 3-18 .

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