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A Practical Approach for Interpreting Multivariate T2 Control Chart Signals

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References

1996Multivariate SPC Methods for Process and Product Monitoring676 cited
1995Decomposition of T 2 for Multivariate Control Chart Interpretation397 cited
1985Multivariate quality control296 cited

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2006On‐line Identification and Quantification of Mean Shifts in Bivariate Processes using a Neural Network‐based Approach85 cited
2005A multivariate EWMA control chart for monitoring process variability with individual observations79 cited

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2001Applying Hotelling'sT2 Statistic to Batch Processes77 cited

2004Artificial neural networks to classify mean shifts from multivariate χ2 chart signals72 cited

1999Improving the Sensitivity of the T 2 Statistic in Multivariate Process Control70 cited

2002Mean shifts detection and classification in multivariate process: a neural-fuzzy approach67 cited

2008An effective application of decision tree learning for on-line detection of mean shifts in multivariate control charts62 cited