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Monitoring and diagnosing of mean shifts in multivariate manufacturing processes using two-level selective ensemble of learning vector quantization neural networks

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References

1983Simulation Modeling and Analysis.8,697 cited
1992A Multivariate Exponentially Weighted Moving Average Control Chart1,231 cited
2000Statistical Methods for Quality Improvement750 cited
1988Multivariate Generalizations of Cumulative Sum Quality-Control Schemes720 cited
1947Multivariate Quality Control549 cited
1990Comparisons of MultivariateCUSUMCharts520 cited
1985Multivariate quality control296 cited
1990Statistical Methods for Quality Improvement165 cited
2005Fault Diagnosis in Multivariate Control Charts Using Artificial Neural Networks128 cited
1993Back-propagation pattern recognizers for control charts: Methodology and performance127 cited
1993X¯ CONTROL CHART PATTERN IDENTIFICATION THROUGH EFFICIENT OFF-LINE NEURAL NETWORK TRAINING104 cited
2007A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes96 cited
2009A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks89 cited
2006On‐line Identification and Quantification of Mean Shifts in Bivariate Processes using a Neural Network‐based Approach85 cited
1999

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A neural network approach to characterize pattern parameters in process control charts

73 cited

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

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2023The partitioning ensemble control chart for on-line monitoring of high-dimensional image-based quality characteristics22 cited