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Improved Monitoring of Multivariate Process Variability

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References

2001Introduction to Statistical Quality Control770 cited
1999Research Issues and Ideas in Statistical Process Control631 cited
1995Decomposition of T 2 for Multivariate Control Chart Interpretation397 cited
1996A Comparison of Multivariate Control Charts for Individual Observations258 cited
1994Multivariate statistical process control—recent results and directions for future research166 cited
1997Assessment of Multivariate Process Control Techniques127 cited

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2009New capability indices for evaluating the performance of multivariate manufacturing processes73 cited
2007Step-Down Analysis for Changes in the Covariance Matrix and Other Parameters50 cited
2008Multivariate Process Variability Monitoring50 cited
2008Multivariate EWMA control charts using individual observations for process mean and variance monitoring and diagnosis45 cited
2008A Multivariate Synthetic Control Chart for Process Dispersion45 cited
2009Monitoring Variation in a Multivariate Process When the Dimension is Large Relative to the Sample Size35 cited
2019Tr(R 2 ) control charts based on kernel density estimation for monitoring multivariate variability process23 cited
2011Effective Control Charts for Monitoring Multivariate Process Dispersion

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21 cited

2021The effectiveness of Max‐half‐Mchart over Max‐Mchart in simultaneously monitoring process mean and variability of individual observations20 cited

2007Statistical Process Control for Variance Shift Detections of Multivariate Autocorrelated Processes19 cited

2021A new multivariate CUSUM chart for monitoring of covariance matrix with individual observations under estimated parameter17 cited

2018A control scheme for monitoring process covariance matrices with more variables than observations16 cited

2025Multivariate Statistical Process Control16 cited

2011Estimation of Change Point in Generalized Variance Control Chart15 cited

2010A Multivariate Process Variability Monitoring Based on Individual Observations15 cited

2008Multivariate Process Variability Monitoring Through Projection12 cited