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Quality Technology & Quantitative Management Volume 3, 2006 - Issue 3
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Original Articles

A Single EWMA Chart for Monitoring Process Mean and Process Variance

A. F. B. CostaDepartment of Production, UNESP-Sao Paulo State University, Guaratingueta, SP, BrazilView further author information
&
M. A. RahimFaculty of Administration, University of New Brunswick, Fredericton, NB, CanadaView further author information
Pages 295-305 | Received 01 Jan 2013, Accepted 01 Aug 2013, Published online: 09 Feb 2016

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Kashinath Chatterjee, Christos Koukouvinos, Angeliki Lappa & Paraskevi Roupa. (2023) A joint monitoring of the process mean and variance with a generally weighted moving average maximum control chart. Communications in Statistics - Simulation and Computation 0:0, pages 1-21.
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Kashinath Chatterjee, Christos Koukouvinos & Angeliki Lappa. (2023) Monitoring process mean and dispersion with one double generally weighted moving average control chart. Journal of Applied Statistics 50:1, pages 19-42.
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Afshan Riaz, Muhammad Noor-ul-Amin & Eralp Dogu. (2022) Effect of measurement error on joint monitoring of process mean and coefficient of variation. Communications in Statistics - Theory and Methods 51:19, pages 6863-6882.
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Farah Arif, Muhammad Noor-ul-Amin & Muhammad Hanif. (2022) Joint monitoring of mean and variance under double ranked set sampling using likelihood ratio test statistic. Communications in Statistics - Theory and Methods 51:17, pages 6032-6048.
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Afshan Riaz & Muhammad Noor-ul-Amin. (2022) Improved simultaneous monitoring of mean and coefficient of variation under ranked set sampling schemes. Communications in Statistics - Simulation and Computation 51:8, pages 4410-4426.
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Kashinath Chatterjee, Christos Koukouvinos & Angeliki Lappa. (2022) A joint monitoring of the process mean and variance with a TEWMA-Max control chart. Communications in Statistics - Theory and Methods 0:0, pages 1-27.
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Kashinath Chatterjee, Christos Koukouvinos & Angeliki Lappa. (2022) Monitoring process mean and variability with one triple EWMA chart. Communications in Statistics - Simulation and Computation 0:0, pages 1-31.
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Imen Baklouti, Majdi Mansouri, Ahmed Ben Hamida, Hazem Numan Nounou & Mohamed Nounou. (2021) Enhanced operation of wastewater treatment plant using state estimation-based fault detection strategies. International Journal of Control 94:2, pages 300-311.
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Zhi Song, Yanchun Liu, Zhonghua Li & Jiujun Zhang. (2018) A weighted likelihood ratio test-based chart for monitoring process mean and variability. Journal of Statistical Computation and Simulation 88:7, pages 1415-1436.
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Yanhong Wu. (2017) Detecting changes in a multiparameter exponential family by using adaptive CUSUM procedure. Sequential Analysis 36:4, pages 467-480.
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Chi-Jui Huang. (2015) A New GWMA Control Chart for Monitoring Process Mean and Variability. Communications in Statistics - Theory and Methods 44:18, pages 3841-3856.
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Chi-Jui Huang & Shin-Li Lu. (2015) Considering Taguchi loss function on statistically constrained economic sum of squares exponentially weighted moving average charts. Journal of Statistical Computation and Simulation 85:3, pages 572-586.
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Chi-Jui Huang. (2014) A Sum of Squares Generally Weighted Moving Average Control Chart. Communications in Statistics - Theory and Methods 43:23, pages 5052-5071.
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Su-Fen Yang. (2013) Using a Single Average Loss Control Chart to Monitor Process Mean and Variability. Communications in Statistics - Simulation and Computation 42:7, pages 1549-1562.
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Xin Zhang & Jiujun Zhang. (2013) CUSUM Procedures for Monitoring Process Mean and Variability. Communications in Statistics - Simulation and Computation 42:7, pages 1455-1471.
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Roberto Quinino, A. Costa & Linda Lee Ho. (2012) A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes. Quality Engineering 24:3, pages 423-430.
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Mei Yang, Zhang Wu, Ka Man Lee & Michael B.C. Khoo. (2012) The X control chart for monitoring process shifts in mean and variance. International Journal of Production Research 50:3, pages 893-907.
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Jiujun Zhang, Changliang Zou & Zhaojun Wang. (2011) A New Chart for Detecting the Process Mean and Variability. Communications in Statistics - Simulation and Computation 40:5, pages 728-743.
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MichaelB. C. Khoo, S. Y. Teh & Zhang Wu. (2010) Monitoring Process Mean and Variability with One Double EWMA Chart. Communications in Statistics - Theory and Methods 39:20, pages 3678-3694.
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