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On artificial neural networking-based process monitoring under bootstrapping using runs rules schemes

16 references·1 citing·39 second hopsampled

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References

2001Monitoring Process Mean and Variability with One EWMA Chart236 cited
2009An enhanced adaptive CUSUM control chart188 cited
2000Two Alternatives to the ShewhartXControl Chart159 cited
1994X -bar and R control chart interpretation using neural computing133 cited
2010Enhancing the performance of EWMA charts129 cited
2005Dual CUSUM control schemes for detecting a range of mean shifts128 cited
2010Optimal Design of a CUSUM Chart for a Mean Shift of Unknown Size125 cited
2008Predicting sovereign debt crises using artificial neural networks: A comparative approach120 cited
2011A comparison study of effectiveness and robustness of control charts for monitoring process mean117 cited
2010Improving the performance of CUSUM charts111 cited
1992Identification of change structure in statistical process control99 cited
1991A comparison of neural networks to SPC charts85 cited
2003Design of Runs Rules Schemes81 cited
2008The ModifiedrOut ofmControl Chart73 cited
2012On monitoring process variability under double sampling scheme69 cited
2001

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Control chart pattern recognition using back propagation artificial neural networks

68 cited

Cited by

2023LSTM-based framework with metaheuristic optimizer for manufacturing process monitoring12 cited