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Quality Engineering Volume 19, 2007 - Issue 3
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Original Articles

Comparison of Multivariate Control Charts for Process Dispersion

N. Jose Alberto Vargas Department of Statistics, National University of Colombia, Bogota, ColombiaCorrespondence[email protected]
&
C. Juliana Lagos Department of Statistics, National University of Colombia, Bogota, Colombia
Pages 191-196 | Published online: 10 Sep 2007

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Mohsen Ebadi, Shojaeddin Chenouri, Dennis K. J. Lin & Stefan H. Steiner. (2022) Statistical monitoring of the covariance matrix in multivariate processes: A literature review. Journal of Quality Technology 54:3, pages 269-289.
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Yunfei Ye & Dong Han. (2021) An optimal control chart for finite matrix sequences at some unknown change point. Journal of Applied Statistics 48:9, pages 1628-1643.
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Aamir Saghir. (2015) The bivariate dispersion control charts for non-normal processes. International Journal of Production Research 53:7, pages 1964-1979.
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Eralp Doğu & İpek Deveci Kocakoç. (2013) A Multivariate Change Point Detection Procedure for Monitoring Mean and Covariance Simultaneously. Communications in Statistics - Simulation and Computation 42:6, pages 1235-1255.
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Eralp Doǧu & İpek Deveci Kocakoç. (2011) Estimation of Change Point in Generalized Variance Control Chart. Communications in Statistics - Simulation and Computation 40:3, pages 345-363.
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Articles from other publishers (15)

Nurudeen A. Adegoke, Abdaljbbar Dawod, Olatunde Adebayo Adeoti, Ridwan A. Sanusi & Saddam Akber Abbasi. (2022) Monitoring multivariate coefficient of variation for high‐dimensional processes. Quality and Reliability Engineering International 38:5, pages 2606-2621.
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Jimoh Olawale Ajadi & Inez Maria Zwetsloot. (2020) Should observations be grouped for effective monitoring of multivariate process variability?. Quality and Reliability Engineering International 36:3, pages 1005-1027.
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Richard Osei‐Aning & Saddam Akber Abbasi. (2019) Efficient bivariate EWMA charts for monitoring process dispersion. Quality and Reliability Engineering International 36:1, pages 247-267.
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Jinyu Fan, Lianjie Shu, Honghao Zhao & Hangfai Yeung. (2017) Monitoring multivariate process variability via eigenvalues. Computers & Industrial Engineering 113, pages 269-281.
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Aamir Saghir, Subhabrata Chakraborti & Ishfaq Ahmad. (2017) On the Performance of Phase-I Bivariate Dispersion Charts to Non-Normality. Quality and Reliability Engineering International 33:3, pages 637-656.
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Richard Osei-Aning, Saddam Akber Abbasi & Muhammad Riaz. (2017) Bivariate Dispersion Control Charts for Monitoring Non-Normal Processes. Quality and Reliability Engineering International 33:3, pages 515-529.
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Edwin Dugarte-Peña & Nelfi González-Álvarez. (2016) ROBUSTIFICACIÓN DE LA CARTA DE CONTROL MULTIVARIADA √(|S|) EN LA FASE I DE CONTROL. Revista de la Facultad de Ciencias 5:2, pages 12-37.
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Aamir Saghir, Yousaf Ali Khan & Subha Chakraborti. (2016) The Phase I Dispersion Charts for Bivariate Process Monitoring. Quality and Reliability Engineering International 32:5, pages 1807-1823.
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Kazuya Nishimura, Shun Matsuura & Hideo Suzuki. (2015) Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring. Statistics & Probability Letters 104, pages 7-13.
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Asokan Mulayath Variyath & Jayasankar Vattathoor. (2014) Robust Control Charts for Monitoring Process Variability in Phase I Multivariate Individual Observations. Quality and Reliability Engineering International 30:6, pages 795-812.
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Shabbir Ahmad, Muhammad Riaz, Saddam Akber Abbasi & Zhengyan Lin. (2013) On monitoring process variability under double sampling scheme. International Journal of Production Economics 142:2, pages 388-400.
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Ashkan Shabbak & Habshah Midi. (2012) An Improvement of the Hotelling Statistic in Monitoring Multivariate Quality Characteristics . Mathematical Problems in Engineering 2012, pages 1-15.
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D.R. Prajapati. (2011) A new approach to monitor the process dispersion. International Journal of Quality & Reliability Management 28:3, pages 280-297.
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William Levinson. 2010. Statistical Process Control for Real-World Applications. Statistical Process Control for Real-World Applications 237 240 .
Ashkan Shabbak, Habshah Midi & Mohd Nooh Hassan. (2010) The Performance of Robust Multivariate Statistical Control Charts based on Different Cutoff-points with Sustained Shift in Mean. Journal of Applied Sciences 11:1, pages 56-65.
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