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On increasing the sensitivity of mixed EWMA–CUSUM control charts for location parameter
13 references·13 citing·29 second hop
On increasing the sensitivity of mixed EWMA–CUSUM control charts for location parameter (2015)On increasing the sensitivity of mixed EW…Improved Fast Initial Response Features for Exponentially Weighted Moving Average and Cumulative Sum Control Charts (2013)Improved Fast Initial Respons…Mixed Exponentially Weighted Moving Average–Cumulative Sum Charts for Process Monitoring (2012)Mixed Exponentially Weighted …Improving the performance of CUSUM charts (2010)Improving the performance of …Enhancing the performance of EWMA charts (2010)Enhancing the performance of …Two Alternatives to the ShewhartXControl Chart (2000)Two Alternatives to the Shewh…Fast Initial Response for CUSUM Quality-Control Schemes: Give Your CUSUM A Head Start (2000)Fast Initial Response for CUS…Control Chart Tests Based on Geometric Moving Averages (2000)Control Chart Tests Based on …EWMA Control Charts with Time-Varying Control Limits and Fast Initial Response (1999)EWMA Control Charts with Time…Introduction to Statistical Quality Control (1997)Introduction to Statistical Q…Introduction to Statistical Quality Control (1992)Introduction to Statistical Q…Fast Initial Response for CUSUM Quality-Control Schemes: Give Your CUSUM A Head Start (1982)Fast Initial Response for CUS…Control Chart Tests Based on Geometric Moving Averages (1959)Control Chart Tests Based on …CONTINUOUS INSPECTION SCHEMES (1954)CONTINUOUS INSPECTION SCHEMESSmart Monitoring Solutions for Real‐Time Water pH Regulation in Aquatic Ecotoxicology (2025)Smart Monitoring Solutions fo…Change point detection to analyze air pollution and its economic effects: an exponentially weighted moving average perspective (2025)Change point detection to ana…Generalized new exponentially weighted moving average control charts (NEWMA) for monitoring process dispersion (2023)Generalized new exponentially…New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry (2022)New Hybrid EWMA Charts for Ef…Accelerated failure time model based risk adjusted MA-EWMA control chart (2022)Accelerated failure time mode…Progressive mean exponentially weighted moving average control chart for monitoring the process location (2020)Progressive mean exponentiall…An efficient approach of designing distribution-free exponentially weighted moving average schemes with dynamic fast initial response for joint monitoring of location and scale (2020)An efficient approach of desi…Multivariate Mixed EWMA-CUSUM Control Chart for Monitoring the Process Variance-Covariance Matrix (2019)Multivariate Mixed EWMA-CUSUM…Enhanced generally weighted moving average variance charts for monitoring process variance with individual observations (2019)Enhanced generally weighted m…Auxiliary Information Based Mixed EWMA–CUSUM Mean Control Chart with Measurement Error (2019)Auxiliary Information Based M…On Designing Mixed EWMA Dual-CUSUM Chart With Applications in Petro-Chemical Industry (2018)On Designing Mixed EWMA Dual-…Enhancing the performance of the EWMA control chart for monitoring the process mean using auxiliary information (2018)Enhancing the performance of …A HEWMA-CUSUM control chart for the Weibull distribution (2017)A HEWMA-CUSUM control chart f…Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Robustness to Non-Normality of the Multivariate EWMA Control Chart (2002)The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process Mean (2003)An Approach to the Probability Distribution of Cusum Run Length (1972)Combined Shewhart-CUSUM Quality Control Schemes (1982)CUSUM Charts With Variable Sampling Intervals (1990)Exponentially weighted moving average control schemes with variable sampling intervals (1992)Statistical Process Monitoring and Feedback Adjustment: A Discussion (1992)The Shewhart Control Chart—Tests for Special Causes (1984)Exact Results for Shewhart Control Charts With Supplementary Runs Rules (1987)Evaluating and Improving the Synthetic Control Chart (2002)The Inertial Properties of Quality Control Charts (2005)Statistical Process Control using Shewhart Control Charts with Supplementary Runs Rules (2007)The Exponentially Weighted Moving Average (1986)A Multivariate Exponentially Weighted Moving Average Control Chart (1992)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)Procedures for Reacting to a Change in Distribution (1971)changepoint : An R Package for Changepoint Analysis (2014)Selective review of offline change point detection methods (2019)Time-Series Modeling for Statistical Process Control (1988)Statistical process control as a tool for research and healthcare improvement (2003)A New Hybrid Exponentially Weighted Moving Average Control Chart for Monitoring Process Mean (2012)Mixed CUSUM-EWMA chart for monitoring process dispersion (2016)Homogeneously weighted moving average control chart with an application in substrate manufacturing process (2018)Transforming Non-Normal Data to Normality in Statistical Process Control (1998)EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes (1999)The State of Statistical Process Control as We Proceed into the 21st Century (2000)Detecting a Shift in Fraction Nonconforming Using Run-Length Control Charts with 100% Inspection (1991)Use of risk-adjusted CUSUM and RSPRTcharts for monitoring in medical contexts (2003)
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References

  • 1992Introduction to Statistical Quality Control7,842 cited
  • 1954CONTINUOUS INSPECTION SCHEMES5,731 cited
  • 1959Control Chart Tests Based on Geometric Moving Averages1,544 cited
  • 2000Control Chart Tests Based on Geometric Moving Averages1,252 cited
  • 2000Fast Initial Response for CUSUM Quality-Control Schemes: Give Your CUSUM A Head Start320 cited
  • 1982Fast Initial Response for CUSUM Quality-Control Schemes: Give Your CUSUM A Head Start310 cited
  • 1997Introduction to Statistical Quality Control309 cited
  • 1999EWMA Control Charts with Time-Varying Control Limits and Fast Initial Response218 cited
  • 2012Mixed Exponentially Weighted Moving Average–Cumulative Sum Charts for Process Monitoring201 cited
  • 2000Two Alternatives to the ShewhartXControl Chart159 cited
  • 2010Enhancing the performance of EWMA charts129 cited
  • 2010Improving the performance of CUSUM charts111 cited
  • 2013Improved Fast Initial Response Features for Exponentially Weighted Moving Average and Cumulative Sum Control Charts38 cited

Cited by

  • 2018Enhancing the performance of the EWMA control chart for monitoring the process mean using auxiliary information25 cited
  • 2017

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A HEWMA-CUSUM control chart for the Weibull distribution
23 cited
  • 2019Auxiliary Information Based Mixed EWMA–CUSUM Mean Control Chart with Measurement Error23 cited
  • 2019Multivariate Mixed EWMA-CUSUM Control Chart for Monitoring the Process Variance-Covariance Matrix23 cited
  • 2020An efficient approach of designing distribution-free exponentially weighted moving average schemes with dynamic fast initial response for joint monitoring of location and scale19 cited
  • 2018On Designing Mixed EWMA Dual-CUSUM Chart With Applications in Petro-Chemical Industry13 cited
  • 2019Enhanced generally weighted moving average variance charts for monitoring process variance with individual observations13 cited
  • 2022Accelerated failure time model based risk adjusted MA-EWMA control chart11 cited
  • 2025Change point detection to analyze air pollution and its economic effects: an exponentially weighted moving average perspective10 cited
  • 2025Smart Monitoring Solutions for Real‐Time Water pH Regulation in Aquatic Ecotoxicology9 cited
  • 2022New Hybrid EWMA Charts for Efficient Process Dispersion Monitoring with Application in Automobile Industry9 cited
  • 2020Progressive mean exponentially weighted moving average control chart for monitoring the process location8 cited
  • 2023Generalized new exponentially weighted moving average control charts (NEWMA) for monitoring process dispersion7 cited