Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Using recurrent neural networks to detect changes in autocorrelated processes for quality monitoring

16 references·16 citing·33 second hopsampled

FromToDepth

this work references cited by second hop· second hop is a sample of the most-cited connections

References

1992Introduction to Statistical Quality Control7,842 cited
1978Time Series Analysis: Forecasting and Control.5,299 cited
1971Time Series Analysis, Forecasting and Control.2,771 cited
2001Introduction to Statistical Quality Control770 cited
1988Time-Series Modeling for Statistical Process Control724 cited
1991Some Statistical Process Control Methods for Autocorrelated Data604 cited
1994Run-Length Distributions of Special-Cause Control Charts for Correlated Processes304 cited
1998A Statistical Control Chart for Stationary Process Data189 cited
2000A New SPC Monitoring Method: The ARMA Chart165 cited
1998A review of neural networks for statistical process control151 cited
1992Introduction to Statistical Quality Control (2nd ed.)145 cited
1993Back-propagation pattern recognizers for control charts: Methodology and performance127 cited
1999A neural network based model for abnormal pattern recognition of control charts115 cited
1995The Problem of Misplaced Control Limits113 cited
1999Recognition of control chart concurrent patterns using a neural network approach111 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

1996

A neural fuzzy control chart for detecting and classifying process mean shifts

90 cited

Cited by

2007Modeling and optimization of stencil printing operations: A comparison study88 cited
2016Robust parameter design for the micro-BGA stencil printing process using a fuzzy logic-based Taguchi method51 cited
2016Supply chain relationship quality and performance in technological turbulence: an artificial neural network approach49 cited
2014Economic design of Shewhart control charts for monitoring autocorrelated data with skip sampling strategies48 cited
2012Minimal Euclidean distance chart based on support vector regression for monitoring mean shifts of auto-correlated processes46 cited
2011The use of neural networks in statistical process control charts43 cited
2013Autoregressive coefficient-invariant control chart pattern recognition in autocorrelated manufacturing processes using neural network ensemble42 cited
2011A survey of AI in operations management from 2005 to 200941 cited
2010Simultaneous process mean and variance monitoring using artificial neural networks36 cited
2013A new sampling strategy to reduce the effect of autocorrelation on a control chart32 cited
2012Control charts for monitoring the autocorrelated process parameters: a literature review28 cited
2010Support Vector Regression control charts for multivariate nonlinear autocorrelated processes24 cited
2011A hybrid method of artificial neural networks and simulated annealing in monitoring auto-correlated multi-attribute processes22 cited
2010LRProbcontrol chart based on logistic regression for monitoring mean shifts of auto-correlated manufacturing processes20 cited
2020On autoregressive model selection for the exponentially weighted moving average control chart of residuals in monitoring the mean of autocorrelated processes19 cited
2013Identifying change point of a non-random pattern on control chart using artificial neural networks17 cited