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Monitoring the Weibull Shape Parameter by Control Charts for the Sample Range of Type II Censored Data
6 references·16 citing·41 second hop
Monitoring the Weibull Shape Parameter by Control Charts for the Sample Range of Type II Censored Data (2011)Monitoring the Weibull Shape Parameter by…EWMA Charts for Monitoring the Mean of Censored Weibull Lifetimes (2004)EWMA Charts for Monitoring th…Detecting Changes in the Mean from Censored Lifetime Data (2001)Detecting Changes in the Mean…Monitoring Processes with Highly Censored Data (2000)Monitoring Processes with Hig…Statistical Quality Assurance Methods for Engineers (1999)Statistical Quality Assurance…Shewhart control charts for the scale parameter of a Weibull control variable with fixed and variable sampling intervals (1999)Shewhart control charts for t…Shewhart-Type Charts for Percentiles of Strength Distributions (1990)Shewhart-Type Charts for Perc…Monitoring the Weibull shape parameter under progressive censoring in presence of independent competing risks (2021)Monitoring the Weibull shape …EWMA and adaptive EWMA variable sampling intervals charts for simultaneous monitoring of Weibull parameters (2021)EWMA and adaptive EWMA variab…Phase-II monitoring of exponentially distributed process based on Type-II censored data for a possible shift in location–scale (2020)Phase-II monitoring of expone…CEV-Hybrid Dewma charts for censored data using Weibull distribution (2019)CEV-Hybrid Dewma charts for c…DEWMA control charts for censored data using R ayleigh lifetimes (2018)DEWMA control charts for cens…Control Chart for Failure-Censored Reliability Tests under Uncertainty Environment (2018)Control Chart for Failure-Cen…A new variable control chart under failure‐censored reliability tests for Weibull distribution (2018)A new variable control chart …The performance of semi-empirical Bayesian control charts for monitoring Weibull data (2017)The performance of semi-empir…New control charts for monitoring the Weibull percentiles under complete data and Type‐II censoring (2017)New control charts for monito…A Study of Control Chart for Monitoring Exponentially Distributed Characteristics Based On Type‐II Censored Samples (2017)A Study of Control Chart for …Monitoring censored lifetime data with a weighted-likelihood scheme (2016)Monitoring censored lifetime …MaxEWMA Control Chart for a Weibull Process with Individual Measurements (2016)MaxEWMA Control Chart for a W…Moving range EWMA control charts for monitoring the Weibull shape parameter (2014)Moving range EWMA control cha…Monitoring the Shape Parameter of a Weibull Regression Model in Phase II Processes (2014)Monitoring the Shape Paramete…ARL-unbiased control charts for the monitoring of exponentially distributed characteristics based on type-II censored samples (2014)ARL-unbiased control charts f…A Shewhart‐type Control Scheme to Monitor Weibull Data without Subgrouping (2013)A Shewhart‐type Control Schem…Statistical Methods for Quality Improvement (1990)The Effect of Sample Size on Estimated Limits forXandXControl Charts (1993)Statistical Methods for Quality Improvement (2000)Monitoring Processes with Data Censored Owing to Competing Risks by Using Exponentially Weighted Moving Average Control Charts (2001)Minimizing the cost of integrated systems approach to process control and maintenance model by EWMA control chart using genetic algorithm (2010)CUSUM Charts for Monitoring the Characteristic Life of Censored Weibull Lifetimes (2014)Introduction to Statistical Quality Control (1992)EWMA Control Chart for Poisson–Exponential Lifetime Distribution Under Type I Censoring (2015)Recent Advances and Future Directions for Quality Engineering (2015)A Simple Method for Studying Run – Length Distributions of Exponentially Weighted Moving Average Charts (1987)Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Monitoring the Weibull shape parameter by control charts for the sample range (2010)Statistical Process Control (2012)Shewhart Control Charts for Monitoring Reliability with Weibull Lifetimes (2014)The performance of control charts for monitoring process variation (1995)A HEWMA-CUSUM control chart for the Weibull distribution (2017)Simultaneously monitoring frequency and magnitude of events based on bivariate gamma distribution (2017)Modified EWMA control chart for transformed gamma data (2019)Cumulative Sum Charts and Charting for Quality Improvement (1998)The Changepoint Model for Statistical Process Control (2003)Effects of Parameter Estimation on Control Chart Properties: A Literature Review (2006)A Phase II control chart based on the weighted likelihood ratio test for monitoring polynomial profiles (2019)An Approach to the Probability Distribution of Cusum Run Length (1972)A Bootstrap Control Chart for Weibull Percentiles (2005)EWMA and DEWMA repetitive control charts under non-normal processes (2020)Nonparametric quality control charts based on the sign statistic (1995)Variables Sampling Plans for Weibull Distributed Lifetimes Under Sudden Death Testing (2006)Economic design of a CEV x control chart for determining optimal right-censored times (2021)The Effect of Non-Normality on the Control Limits of X Charts (1976)Average Run Lengths for CUSUM Schemes When Observations Are Exponentially Distributed (1985)Counted Data CUSUM's (1985)On the α-risks for shewhart control charts (1992)EWMA Charts for the Weibull Shape Parameter (2010)Control Charts For Monitoring The Weibull Shape Parameter Based On Type‐II Censored Sample (2012)An EWMA for Monitoring a Process Standard Deviation (1992)Introduction to Statistical Quality Control (2001)The Performance of Exponentially Weighted Moving Average Charts With Estimated Parameters (2001)A study of EWMA chart with transformed exponential data (2006)On t and EWMA t charts for monitoring changes in the process mean (2009)Monitoring Process Mean and Variability with One Double EWMA Chart (2010)Adaptive Thresholds (2006)
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References

  • 2004EWMA Charts for Monitoring the Mean of Censored Weibull Lifetimes113 cited
  • 1999Statistical Quality Assurance Methods for Engineers84 cited
  • 2000Monitoring Processes with Highly Censored Data78 cited
  • 1990Shewhart-Type Charts for Percentiles of Strength Distributions72 cited
  • 2001Detecting Changes in the Mean from Censored Lifetime Data52 cited
  • 1999Shewhart control charts for the scale parameter of a Weibull control variable with fixed and variable sampling intervals51 cited

Cited by

  • 2014Moving range EWMA control charts for monitoring the Weibull shape parameter35 cited
  • 2017New control charts for monitoring the Weibull percentiles under complete data and Type‐II censoring31 cited
  • 2016Monitoring censored lifetime data with a weighted-likelihood scheme26 cited
  • 2018A new variable control chart under failure‐censored reliability tests for Weibull distribution26 cited
  • 2018Control Chart for Failure-Censored Reliability Tests under Uncertainty Environment26 cited
  • 2017A Study of Control Chart for Monitoring Exponentially Distributed Characteristics Based On Type‐II Censored Samples22 cited
  • 2019CEV-Hybrid Dewma charts for censored data using Weibull distribution22 cited
  • 2018DEWMA control charts for censored data using R ayleigh lifetimes

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22 cited
  • 2014ARL-unbiased control charts for the monitoring of exponentially distributed characteristics based on type-II censored samples21 cited
  • 2017The performance of semi-empirical Bayesian control charts for monitoring Weibull data19 cited
  • 2021Monitoring the Weibull shape parameter under progressive censoring in presence of independent competing risks19 cited
  • 2020Phase-II monitoring of exponentially distributed process based on Type-II censored data for a possible shift in location–scale18 cited
  • 2021EWMA and adaptive EWMA variable sampling intervals charts for simultaneous monitoring of Weibull parameters14 cited
  • 2016MaxEWMA Control Chart for a Weibull Process with Individual Measurements14 cited
  • 2014Monitoring the Shape Parameter of a Weibull Regression Model in Phase II Processes13 cited
  • 2013A Shewhart‐type Control Scheme to Monitor Weibull Data without Subgrouping13 cited