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Original Articles

Multivariate CUSUM Quality-Control Procedures

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Pages 285-292 | Published online: 23 Mar 2012

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Bo Shen & Zhenyu (James) Kong. (2024) Active defect discovery: A human-in-the-loop learning method. IISE Transactions 56:6, pages 638-651.
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Wei-Heng Huang, Jing Sun & Arthur B. Yeh. (2023) Monitoring and diagnostics of correlated quality variables of different types. Journal of Quality Technology 55:2, pages 220-252.
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Daniel Ashagrie Tegegne, Daniel Kitaw & Eshetie Berhan. (2022) Advances in statistical quality control chart techniques and their limitations to cement industry. Cogent Engineering 9:1.
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Wendong Li, Chi Zhang, Fugee Tsung & Yajun Mei. (2021) Nonparametric monitoring of multivariate data via KNN learning. International Journal of Production Research 59:20, pages 6311-6326.
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Abdul Haq, Michael B. C. Khoo, Ming Ha Lee & Saddam Akber Abbasi. (2021) Enhanced adaptive multivariate EWMA and CUSUM charts for process mean. Journal of Statistical Computation and Simulation 91:12, pages 2361-2382.
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Xiaochen Xian, Chen Zhang, Scott Bonk & Kaibo Liu. (2021) Online monitoring of big data streams: A rank-based sampling algorithm by data augmentation. Journal of Quality Technology 53:2, pages 135-153.
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Jian Li, Qiang Zhou & Dong Ding. (2020) Efficient monitoring of autocorrelated Poisson counts. IISE Transactions 52:7, pages 769-779.
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Moez Farokhnia & S. T. A. Niaki. (2020) Principal component analysis-based control charts using support vector machines for multivariate non-normal distributions. Communications in Statistics - Simulation and Computation 49:7, pages 1815-1838.
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Hoang M. Tran, Satish T. S. Bukkapatnam & Mridul Garg. (2019) Detecting changes in transient complex systems via dynamic network inference. IISE Transactions 51:3, pages 337-353.
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Abdul Haq. (2019) Weighted adaptive multivariate CUSUM charts with variable sampling intervals. Journal of Statistical Computation and Simulation 89:3, pages 478-491.
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Saba Abbasi & Abdul Haq. (2019) Optimal CUSUM and adaptive CUSUM charts with auxiliary information for process mean. Journal of Statistical Computation and Simulation 89:2, pages 337-361.
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María I. Flury & Marta B. Quaglino. (2018) Multivariate EWMA control chart with highly asymmetric gamma distributions. Quality Technology & Quantitative Management 15:2, pages 230-252.
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Jiaqi Chen, Hualong Yang & Jianfeng Yao. (2018) A new multivariate CUSUM chart using principal components with a revision of Crosier's chart. Communications in Statistics - Simulation and Computation 47:2, pages 464-476.
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Xiaochen Xian, Andi Wang & Kaibo Liu. (2018) A Nonparametric Adaptive Sampling Strategy for Online Monitoring of Big Data Streams. Technometrics 60:1, pages 14-25.
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Wenjuan Liang, Xiaolong Pu & Dongdong Xiang. (2017) A distribution-free multivariate CUSUM control chart using dynamic control limits. Journal of Applied Statistics 44:11, pages 2075-2093.
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Wichai Chattinnawat & Canan Bilen. (2017) Performance analysis of hotelling T2 under multivariate inspection errors. Quality Technology & Quantitative Management 14:3, pages 249-268.
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Junjie Wang, Jian Li & Qin Su. (2017) Multivariate Ordinal Categorical Process Control Based on Log-Linear Modeling. Journal of Quality Technology 49:2, pages 108-122.
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Yuhui Chen & Timothy Hanson. (2017) Semiparametric regression control charts. Journal of Statistical Theory and Practice 11:1, pages 126-144.
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Dong Ding, Fugee Tsung & Jian Li. (2016) Rank-based process control for mixed-type data. IIE Transactions 48:7, pages 673-683.
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Kaibo Liu, Yajun Mei & Jianjun Shi. (2015) An Adaptive Sampling Strategy for Online High-Dimensional Process Monitoring. Technometrics 57:3, pages 305-319.
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Mi Lim Lee, David Goldsman & Seong-Hee Kim. (2015) Robust distribution-free multivariate CUSUM charts for spatiotemporal biosurveillance in the presence of spatial correlation. IIE Transactions on Healthcare Systems Engineering 5:2, pages 74-88.
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J. Kim, K.N. Al-Khalifa, M.K. Jeong, A.M.S. Hamouda & E.A. Elsayed. (2014) Multivariate statistical process control charts based on the approximate sequential χ2 test. International Journal of Production Research 52:18, pages 5514-5527.
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Mi Lim Lee, David Goldsman, Seong-Hee Kim & Kwok-Leung Tsui. (2014) Spatiotemporal biosurveillance with spatial clusters: control limit approximation and impact of spatial correlation. IIE Transactions 46:8, pages 813-827.
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Jian Li, Fugee Tsung & Changliang Zou. (2014) Multivariate binomial/multinomial control chart. IIE Transactions 46:5, pages 526-542.
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Shuguang He, Zhen He & G. Alan Wang. (2014) CUSUM Control Charts for Multivariate Poisson Distribution. Communications in Statistics - Theory and Methods 43:6, pages 1192-1208.
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Ick Huh, Román Viveros-Aguilera & Narayanaswamy Balakrishnan. (2013) Differential Smoothing in the Bivariate Exponentially Weighted Moving Average Chart. Journal of Quality Technology 45:4, pages 377-393.
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Ting-Ting Gang, Jun Yang & Yu Zhao. (2013) Multivariate control chart based on the highest possibility region. Journal of Applied Statistics 40:8, pages 1673-1681.
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Shuguang He, Gang Alan Wang, Min Zhang & Deborah F. Cook. (2013) Multivariate process monitoring and fault identification using multiple decision tree classifiers. International Journal of Production Research 51:11, pages 3355-3371.
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Patrícia Ferreira Ramos, Manuel Cabral Morais, António Pacheco & Wolfgang Schmid. (2013) Stochastic Ordering in the Qualitative Assessment of the Performance of Simultaneous Schemes for Bivariate Processes. Sequential Analysis 32:2, pages 214-229.
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M. A. Mahmoud & P. E. Maravelakis. (2013) The performance of multivariate CUSUM control charts with estimated parameters. Journal of Statistical Computation and Simulation 83:4, pages 721-738.
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Kwok-Leung Tsui, Sung Won Han, Wei Jiang & WilliamH. Woodall. (2012) A review and comparison of likelihood-based charting methods. IIE Transactions 44:9, pages 724-743.
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Jian Li, Fugee Tsung & Changliang Zou. (2012) Directional Control Schemes for Multivariate Categorical Processes. Journal of Quality Technology 44:2, pages 136-154.
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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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ShingI. Chang & Shih-Hsiung Chou. (2010) A Visualization Decision Support Tool for Multivariate SPC Diagnosis Using Marginal CUSUM Glyphs. Quality Engineering 22:3, pages 182-198.
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Seoung Bum Kim, Weerawat Jitpitaklert & Thuntee Sukchotrat. (2010) One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes. Communications in Statistics - Simulation and Computation 39:3, pages 461-474.
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MahmoudA. Mahmoud & AlyaaR. Zahran. (2010) A Multivariate Adaptive Exponentially Weighted Moving Average Control Chart. Communications in Statistics - Theory and Methods 39:4, pages 606-625.
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Jianbo Yu & Lifeng Xi. (2009) A hybrid learning-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes. International Journal of Production Research 47:15, pages 4077-4108.
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Kaibo Wang & Wei Jiang. (2009) High-Dimensional Process Monitoring and Fault Isolation via Variable Selection. Journal of Quality Technology 41:3, pages 247-258.
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RobertL. Mason, Youn-Min Chou & JohnC. Young. (2009) Monitoring Variation in a Multivariate Process When the Dimension is Large Relative to the Sample Size. Communications in Statistics - Theory and Methods 38:6, pages 939-951.
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E. Andersson. (2009) Effect of Dependency in Systems for Multivariate Surveillance. Communications in Statistics - Simulation and Computation 38:3, pages 454-472.
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Francisco Aparisi & MarcoA. de Luna. (2009) The Design and Performance of the Multivariate Synthetic-T 2 Control Chart. Communications in Statistics - Theory and Methods 38:2, pages 173-192.
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Muhammad Riaz & RonaldJ. M. M. Does. (2008) An Alternative to the Bivariate Control Chart for Process Dispersion. Quality Engineering 21:1, pages 63-71.
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Isabel González & Ismael Sánchez. (2008) Principal alarms in multivariate statistical process control using independent component analysis. International Journal of Production Research 46:22, pages 6345-6366.
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J. B. Yu & L. F. Xi. (2008) Using an chart based on a self-organizing map NN to monitor out-of-control signals in manufacturing processes. International Journal of Production Research 46:21, pages 5907-5933.
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S. T. A. Niaki & B. Abbasi. (2008) Detection and classification mean-shifts in multi-attribute processes by artificial neural networks. International Journal of Production Research 46:11, pages 2945-2963.
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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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Isabel González & Ismael Sánchez. (2008) Principal Alarms in Multivariate Statistical Process Control. Journal of Quality Technology 40:1, pages 19-30.
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Seyed Taghi Akhavan Niaki & Babak Abbasi. (2007) Skewness Reduction Approach in Multi-Attribute Process Monitoring. Communications in Statistics - Theory and Methods 36:12, pages 2313-2325.
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Young Soon Chang. (2007) Multivariate CUSUM and EWMA Control Charts for Skewed Populations Using Weighted Standard Deviations. Communications in Statistics - Simulation and Computation 36:4, pages 921-936.
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Longcheen Huwang, Arthur B. Yeh & Chien-Wei Wu. (2007) Monitoring Multivariate Process Variability for Individual Observations. Journal of Quality Technology 39:3, pages 258-278.
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Vasyl Golosnoy & Wolfgang Schmid. (2007) EWMA Control Charts for Monitoring Optimal Portfolio Weights. Sequential Analysis 26:2, pages 195-224.
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CharlesW. Champ & L. Allison Jones-Farmer. (2007) Properties of Multivariate Control Charts with Estimated Parameters. Sequential Analysis 26:2, pages 153-169.
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George C. Runger, Russell R. Barton, Enrique Del Castillo & William H. Woodall. (2007) Optimal Monitoring of Multivariate Data for Fault Patterns. Journal of Quality Technology 39:2, pages 159-172.
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Francisco Aparisi, Gerardo Avendaño & JosÉ Sanz. (2006) Techniques to interpret T 2 control chart signals. IIE Transactions 38:8, pages 647-657.
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Covariance Matrix, Marion R. Reynolds$suffix/text()$suffix/text() & Gyo-Young Cho. (2006) Multivariate Control Charts for Monitoring the Mean Vector and Covariance Matrix. Journal of Quality Technology 38:3, pages 230-253.
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E. Andersson, D. Bock & M. Frisén. (2006) Some statistical aspects of methods for detection of turning points in business cycles. Journal of Applied Statistics 33:3, pages 257-278.
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William H. Woodall. (2006) The Use of Control Charts in Health-Care and Public-Health Surveillance. Journal of Quality Technology 38:2, pages 89-104.
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Shiyu Zhou, Nong Jin & Jionghua (Judy) Jin. (2005) Cycle-based signal monitoring using a directionally variant multivariate control chart system. IIE Transactions 37:11, pages 971-982.
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Arthur B. Yeh, Longcheen Huwang & Chien-Wei Wu. (2005) A multivariate EWMA control chart for monitoring process variability with individual observations. IIE Transactions 37:11, pages 1023-1035.
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Keunpyo Kim & Marion R. Reynolds$suffix/text()$suffix/text(). (2005) Multivariate Monitoring Using an MEWMA Control Chart with Unequal Sample Sizes. Journal of Quality Technology 37:4, pages 267-281.
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DAVID HE & ARSEN GRIGORYAN. (2005) Multivariate multiple sampling charts. IIE Transactions 37:6, pages 509-521.
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Yee Cheong Lam , M. Shamsuzzaman, Sheng Zhang & Zhang Wu. (2005) Integrated control chart system—optimization of sample sizes, sampling intervals and control limits. International Journal of Production Research 43:3, pages 563-582.
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ARTHURB. YEH, LONGCHEEN HUWANG & YU-FANG WU. (2004) A likelihood-ratio-based EWMA control chart for monitoring variability of multivariate normal processes. IIE Transactions 36:9, pages 865-879.
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ZHANG WU, YEE CHEONG LAM, SHENG ZHANG & M. SHAMSUZZAMAN. (2004) Optimization design of control chart systems. IIE Transactions 36:5, pages 447-455.
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Srinivas Talluri & Joseph Sarkis. (2002) A methodology for monitoring system performance. International Journal of Production Research 40:7, pages 1567-1582.
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T. C. Chang & F. F. Gan. (2001) Detecting over Rejection in Testing of Integrated Circuits. Journal of Quality Technology 33:3, pages 356-364.
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DOGANA. SEREL, HERBERT MOSKOWITZ & JEN TANG. (2000) Univariate X¯control charts for individual characteristics in a multinomial model. IIE Transactions 32:12, pages 1115-1125.
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Lan Kang & Susan L. Albin. (2000) On-Line Monitoring When the Process Yields a Linear Profile. Journal of Quality Technology 32:4, pages 418-426.
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Manuel Cabral Morais & António Pacheco. (2000) On the performance of combined EWMA schemes for μ and σ: a markovian approach. Communications in Statistics - Simulation and Computation 29:1, pages 153-174.
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FUGEE TSUNG & JIANJUN SHI. (1999) Integrated design of run-to-run PID controller and SPC monitoring for process disturbance rejection. IIE Transactions 31:6, pages 517-527.
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Kevin M. Bodden & Steven E. Rigdon. (1999) A Program for Approximating the In-Control ARL for the MEWMA Chart. Journal of Quality Technology 31:1, pages 120-123.
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NIKIFOROS T. LAOPODIS. (1999) Optimal prediction rule: an application to debt reschedulings. Applied Economics 31:1, pages 17-26.
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Peter Wessman. (1998) Some principles for surveillance adopted for multivariate processes with a common change point. Communications in Statistics - Theory and Methods 27:5, pages 1143-1161.
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Douglas C. Montgomery & William H. Woodall. (1997) Concluding Remarks. Journal of Quality Technology 29:2, pages 157-162.
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GeorgeC. Runger & SharadS. Prabhu. (1996) A Markov Chain Model for the Multivariate Exponentially Weighted Moving Averages Control Chart. Journal of the American Statistical Association 91:436, pages 1701-1706.
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George C. Runger. (1996) Projections and the U2 Multivariate Control Chart. Journal of Quality Technology 28:3, pages 313-319.
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CYNTHIAA. LOWRY & DOUGLASC. MONTGOMERY. (1995) A review of multivariate control charts. IIE Transactions 27:6, pages 800-810.
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Steven E. Rigdon. (1995) An integral equation for the in-control average run length of a multivariate exponentially weighted moving average control chart. Journal of Statistical Computation and Simulation 52:4, pages 351-365.
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Robert L. Mason, Nola D. Tracy & John C. Young. (1995) Decomposition of T2 for Multivariate Control Chart Interpretation. Journal of Quality Technology 27:2, pages 99-108.
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Anthony J. Hayter & Kwok-Leung Tsui. (1994) Identification and Quantification in Multivariate Quality Control Problems. Journal of Quality Technology 26:3, pages 197-208.
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Camil Fuchs & Yoav Benjamini. (1994) Multivariate Profile Charts for Statistical Process Control. Technometrics 36:2, pages 182-195.
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Douglas M. Hawkins. (1993) Regression Adjustment for Variables in Multivariate Quality Control. Journal of Quality Technology 25:3, pages 170-182.
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PanayiotisT. Theodossiou. (1993) Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures. Journal of the American Statistical Association 88:422, pages 441-449.
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Kwok-Leung Tsui & William H. Woodall. (1993) Multivariate control charts based on loss functions. Sequential Analysis 12:1, pages 79-92.
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CynthiaA. Lowry, WilliamH. Woodall, CharlesW. Champ & StevenE. Rigdon. (1992) A Multivariate Exponentially Weighted Moving Average Control Chart. Technometrics 34:1, pages 46-53.
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DouglasM. Hawkins. (1991) Multivariate Quality Control Based on Regression-Adiusted Variables. Technometrics 33:1, pages 61-75.
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Necip Doganaksoy, Frederick W. Faltin & William T. Tucker. (1991) Identification of out of control quality characteristics in a multivariate manufacturing environment. Communications in Statistics - Theory and Methods 20:9, pages 2775-2790.
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Joseph J. Pignatiello$suffix/text()$suffix/text() & George C. Runger. (1990) Comparisons of Multivariate CUSUM Charts. Journal of Quality Technology 22:3, pages 173-186.
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RonaldB. Crosier. (1988) Multivariate Generalizations of Cumulative Sum Quality-Control Schemes. Technometrics 30:3, pages 291-303.
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JohnD. Healy. (1987) A Note on Multivariate CUSUM Procedures. Technometrics 29:4, pages 409-412.
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William H. Woodall. (1986) The Design of CUSUM Quality Control Charts. Journal of Quality Technology 18:2, pages 99-102.
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Kwami Tuprah & William H. Woodall. (1986) Bivariate dispersion quality control charts. Communications in Statistics - Simulation and Computation 15:2, pages 505-522.
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