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An Improved Hidden Markov Model for Monitoring the Process with Autocorrelated Observations
16 references·0 citing·33 second hop
An Improved Hidden Markov Model for Monitoring the Process with Autocorrelated Observations (2022)An Improved Hidden Markov Model for Monit…An interval probability‐based FMEA model for risk assessment: A real‐world case (2019)An interval probability‐based…A multi-variable grey model with a self-memory component and its application on engineering prediction (2015)A multi-variable grey model w…Using recurrent neural networks to detect changes in autocorrelated processes for quality monitoring (2007)Using recurrent neural networ…Using vector autoregressive residuals to monitor multivariate processes in the presence of serial correlation (2006)Using vector autoregressive r…Cusum Charts for Monitoring an Autocorrelated Process (2001)Cusum Charts for Monitoring a…A New SPC Monitoring Method: The ARMA Chart (2000)A New SPC Monitoring Method: …EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes (1999)EWMA Control Charts for Monit…Detection capability of residual control chart for stationary process data (1997)Detection capability of resid…SPC with correlated observations for the chemical and process industries (1995)SPC with correlated observati…On the run length of a Shewhart chart for correlated data (1995)On the run length of a Shewha…Run-Length Distributions of Special-Cause Control Charts for Correlated Processes (1994)Run-Length Distributions of S…Performance of CUSUM Control Schemes for Serially Correlated Observations (1993)Performance of CUSUM Control …The effect of autocorrelation on the retrospectiveX-chart (1992)The effect of autocorrelation…Control Charts in the Presence of Data Correlation (1992)Control Charts in the Presenc…Some Statistical Process Control Methods for Autocorrelated Data (1991)Some Statistical Process Cont…Modification of Control Chart Limits in the Presence of Data Correlation (1978)Modification of Control Chart…Time Series Analysis Forecasting and Control. (1971)Time-Series Modeling for Statistical Process Control (1988)Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)The State of Statistical Process Control as We Proceed into the 21st Century (2000)A Rank-Based Multivariate CUSUM Procedure (2001)The Performance of Exponentially Weighted Moving Average Charts With Estimated Parameters (2001)Time Series Analysis: Forecasting and Control (1977)Introduction to Statistical Quality Control (1992)Brocess capability with asymmetric tolerances (1994)Research Issues and Ideas in Statistical Process Control (1999)Controversies and Contradictions in Statistical Process Control (2000)Time Series Analysis: Forecasting and Control (1977)A Cumulative Sum Control Chart for Monitoring Process Variance (1995)Robustness to non-normality and autocorrelation of individuals control charts (2000)CONTINUOUS INSPECTION SCHEMES (1954)Extreme Values, Regular Variation and Point Processes (1987)The Asymptotic Theory of Extreme Order Statistics (1990)Monitoring Processes That Wander Using Integrated Moving Average Models (1996)The GLRT for statistical process control of autocorrelated processes (1999)An Approach to the Probability Distribution of Cusum Run Length (1972)Control Charts for Time Series: A Review (2004)A Markov Chain Model for the Adaptive CUSUM Control Chart (2006)SPC Procedures for Monitoring Autocorrelated Processes (2007)The Exponentially Weighted Moving Average (1986)Control Chart Tests Based on Geometric Moving Averages (2000)Statistical process control procedures for correlated observations (1991)The AutoregressiveT2 Chart for Monitoring Univariate Autocorrelated Processes (2002)Effects of autocorrelation on control chart performance (1992)A Statistical Control Chart for Stationary Process Data (1998)A Reference-Free Cuscore Chart for Dynamic Mean Change Detection and a Unified Framework for Charting Performance Comparison (2006)Control Charts for Monitoring the Mean and Variance of Autocorrelated Processes (1999)Variable Sampling IntervalXCharts in the Presence of Correlation (1996)EVVMA and cusum control charts in the presence of correlation (1997)
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References

  • 1991Some Statistical Process Control Methods for Autocorrelated Data604 cited
  • 1994Run-Length Distributions of Special-Cause Control Charts for Correlated Processes304 cited
  • 1999EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes303 cited
  • 1978Modification of Control Chart Limits in the Presence of Data Correlation236 cited
  • 1992Control Charts in the Presence of Data Correlation178 cited
  • 1993Performance of CUSUM Control Schemes for Serially Correlated Observations166 cited
  • 2000A New SPC Monitoring Method: The ARMA Chart165 cited
  • 2001Cusum Charts for Monitoring an Autocorrelated Process152 cited
  • 1992The effect of autocorrelation on the retrospectiveX-chart121 cited
  • 1995On the run length of a Shewhart chart for correlated data104 cited
  • 1995SPC with correlated observations for the chemical and process industries77 cited
  • 2015A multi-variable grey model with a self-memory component and its application on engineering prediction72 cited
  • 2006Using vector autoregressive residuals to monitor multivariate processes in the presence of serial correlation57 cited
  • 1997Detection capability of residual control chart for stationary process data56 cited
  • 2007

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Using recurrent neural networks to detect changes in autocorrelated processes for quality monitoring
56 cited
  • 2019An interval probability‐based FMEA model for risk assessment: A real‐world case56 cited
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