A generally weighted moving average control chart for monitoring the coefficient of variation
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[1] Jih-Gau Juang,et al. Disturbance encountered landing system design based on sliding mode control with evolutionary computation and cerebellar model articulation controller , 2015 .
[2] Zhonghua Li,et al. Necessary and sufficient conditions for non-interaction of a pair of one-sided EWMA schemes with reflecting boundaries , 2009 .
[3] D. Barr,et al. Mean and Variance of Truncated Normal Distributions , 1999 .
[4] Raymond H. Myers,et al. On the percentage points of the sample coefficient of variation , 1968 .
[5] Min Xie,et al. Rank-based EWMA procedure for sequentially detecting changes of process location and variability , 2018 .
[6] N. Pal,et al. A note on interval estimation of the standard deviation of a gamma population with applications to statistical quality control , 2013 .
[7] Peihua Qiu. Introduction to Statistical Process Control , 2013 .
[8] Philippe Castagliola,et al. A Control Chart for the Multivariate Coefficient of Variation , 2016, Qual. Reliab. Eng. Int..
[9] Chi-Jui Huang. A Sum of Squares Generally Weighted Moving Average Control Chart , 2014 .
[10] Shey-Huei Sheu,et al. The Generally Weighted Moving Average Control Chart for Monitoring the Process Median , 2006 .
[11] Maria E. Calzada,et al. A synthetic control chart for the coefficient of variation , 2013 .
[12] Shey-Huei Sheu,et al. Generally weighted moving average control chart for monitoring process variability , 2006 .
[13] Zhonghua Li,et al. Control chart for monitoring the coefficient of variation with an exponentially weighted moving average procedure , 2018, Qual. Reliab. Eng. Int..
[14] Peihua Qiu,et al. Distribution-free multivariate process control based on log-linear modeling , 2008 .
[15] Peihua Qiu,et al. Statistical Process Control Using a Dynamic Sampling Scheme , 2014, Technometrics.
[16] Eui-Pyo Hong,et al. Development of CV Control Chart Using EWMA Technique , 2008 .
[17] Giovanni Celano,et al. Monitoring the Coefficient of Variation Using a Variable Sampling Interval Control Chart , 2013, Qual. Reliab. Eng. Int..
[18] Gorjan Alagic,et al. #p , 2019, Quantum information & computation.
[19] P. Alam. ‘G’ , 2021, Composites Engineering: An A–Z Guide.
[20] Changliang Zou,et al. The computation of average run length and average time to signal: an overview , 2014 .
[21] Giovanni Celano,et al. Monitoring the Coefficient of Variation Using EWMA Charts , 2011 .
[22] Robert Breunig,et al. An almost unbiased estimator of the coefficient of variation , 2001 .
[23] N. Balakrishnan,et al. A generally weighted moving average chart for time between events , 2017 .
[24] Philippe Castagliola,et al. Monitoring the Coefficient of Variation Using the Side Sensitive Group Runs Chart , 2016, Qual. Reliab. Eng. Int..
[25] Giovanni Celano,et al. Monitoring the coefficient of variation using a variable sample size control chart in short production runs , 2015, The International Journal of Advanced Manufacturing Technology.
[26] Giovanni Celano,et al. One-Sided Shewhart-type Charts for Monitoring the Coefficient of Variation in Short Production Runs , 2015 .
[27] Douglas M. Hawkins,et al. A Control Chart for the Coefficient of Variation , 2007 .
[28] Bin Chen,et al. A new exponentially weighted moving average control chart for monitoring the coefficient of variation , 2014, Comput. Ind. Eng..
[29] Wei Jiang,et al. A New EWMA Chart for Monitoring Process Dispersion , 2008 .
[30] Giovanni Celano,et al. Monitoring the Coefficient of Variation Using Control Charts with Run Rules , 2013 .
[31] Shey-Huei Sheu,et al. The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process Mean , 2003 .
[32] N. Kumaresan. Optimal control for stochastic linear quadratic singular periodic neuro Takagi–Sugeno (T-S) fuzzy system with singular cost using ant colony programming , 2011 .