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Monitoring high-yields processes with defects count in nonconforming items by artificial neural network
12 references·1 citing·41 second hop
Monitoring high-yields processes with defects count in nonconforming items by artificial neural network (2006)Monitoring high-yields processes with def…Fault Diagnosis in Multivariate Control Charts Using Artificial Neural Networks (2005)Fault Diagnosis in Multivaria…Improved p charts to monitor process quality (1999)Improved p charts to monitor …A neural network based model for abnormal pattern recognition of control charts (1999)A neural network based model …The use of probability limits for process control based on geometric distribution (1997)The use of probability limits…Control Charts Based on Attribute Data: Bibliography and Review (1997)Control Charts Based on Attri…A neural network approach for the analysis of control chart patterns (1997)A neural network approach for…Control charts for processes subject to random shocks (1995)Control charts for processes …A Control Chart for Parts-Per-Million Nonconforming Items (1994)A Control Chart for Parts-Per…‘On‐line’G‐control chart for attribute data (1994)‘On‐line’G‐control chart for …Spc of a near zero‐defect process subject to random shocks (1993)Spc of a near zero‐defect pro…Statistical Control Charts Based on a Geometric Distribution (1992)Statistical Control Charts Ba…Some procedures for decision making in controlling high yield processes (1992)Some procedures for decision …Approximate distribution of demerit statistic—A bounding approach (2007)Approximate distribution of d…Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)A Multivariate Exponentially Weighted Moving Average Control Chart (1992)Introduction to Statistical Quality Control (1992)A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes (2007)A neural network applied to estimate process capability of non-normal processes (2008)Recognition of concurrent control chart patterns using wavelet transform decomposition and multiclass support vector machines (2013)Counted Data CUSUM's (1985)Statistical Quality Control (1989)Statistical Quality Control (1990)A Review and perspective on surveillance of Bernoulli processes (2011)Economic Control of Quality of Manufactured Product. (1932)Statistical techniques for quality (1999)Statistical Methods for Quality Improvement (2000)A CCC‐r chart for high‐yield processes (2001)Control Charts for Dispersed Count Data: An Overview (2014)Control Charts and Stochastic Processes (1959)Quality Control and Industrial Statistics. (1967)SPC Q Charts for a Binomial Parameter p : Short or Long Runs (1991)A quality monitoring and decision‐making scheme for automated production processes (1999)Design of the sum-of-conforming-run-length control charts (2001)Simulation Modeling and Analysis. (1983)A control chart pattern recognition system using a statistical correlation coefficient method (2005)A cost-sensitive convolution neural network learning for control chart pattern recognition (2020)Introduction to Statistical Quality Control. (1986)Detecting a Shift in Fraction Nonconforming Using Run-Length Control Charts with 100% Inspection (1991)Statistical Quality Control Methods in Infection Control and Hospital Epidemiology, Part I Introduction and Basic Theory (1998)Statistical Quality Control Methods in Infection Control and Hospital Epidemiology, Part II: Chart Use, Statistical Properties, and Research Issues (1998)Control Charts Based on the Exponential Distribution: Adapting Runs Rules for the t Chart (2013)CONTINUOUS INSPECTION SCHEMES (1954)The Economic Design of Control Charts: A Unified Approach (1986)Quality Engineering in Production Systems (1990)Research Issues and Ideas in Statistical Process Control (1999)The Use of Control Charts in Health-Care and Public-Health Surveillance (2006)Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications (2014)The Shewhart Control Chart—Tests for Special Causes (1984)Some Current Directions in the Theory and Application of Statistical Process Monitoring (2014)A review of neural networks for statistical process control (1998)A survey of control-chart pattern-recognition literature (1991–2010) based on a new conceptual classification scheme (2012)Control chart pattern recognition using the convolutional neural network (2019)CUSUM charts for monitoring a zero‐inflated poisson process (2011)Generalized linear model based monitoring methods for high‐yield processes (2020)
this work references cited by second hop

References

  • 1997Control Charts Based on Attribute Data: Bibliography and Review266 cited
  • 1992Statistical Control Charts Based on a Geometric Distribution180 cited
  • 1994A Control Chart for Parts-Per-Million Nonconforming Items171 cited
  • 1997A neural network approach for the analysis of control chart patterns169 cited
  • 2005Fault Diagnosis in Multivariate Control Charts Using Artificial Neural Networks128 cited
  • 1999A neural network based model for abnormal pattern recognition of control charts115 cited
  • 1992Some procedures for decision making in controlling high yield processes81 cited
  • 1997The use of probability limits for process control based on geometric distribution77 cited
  • 1993Spc of a near zero‐defect process subject to random shocks66 cited
  • 1994‘On‐line’G‐control chart for attribute data63 cited
  • 1999Improved p charts to monitor process quality55 cited
  • 1995Control charts for processes subject to random shocks32 cited

Cited by

  • 2007Approximate distribution of demerit statistic—A bounding approach7 cited

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