Control charting and survey sampling techniques in process monitoring

Muhammad Riaz

33 citations0/0 files storedJournal of the Chinese Institute of Engineers

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Survey Sampling and Estimation Techniques

Abstract

Control charts are widely used for the detection of shifts in process parameters. In this study, we propose some enhanced Shewhart-type control charts using improved estimators based on auxiliary characteristics. A general control charting structure is developed that can be used with different location estimators. Performance of the proposed charts is compared using average run length (ARL), extra quadratic loss (EQL), and relative average run length (RARL) as performance measures. Comparisons are made among different proposals and the existing counterparts. It is observed that the proposed charts offer improved detection abilities depending upon the correlation structures among different variables under consideration. An illustrative example is also included to highlight the applications in practical situations.

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References

1992Introduction to Statistical Quality Control 2007Introduction to Statistical Quality Control 1993Regression Adjustment for Variables in Multivariate Quality Control 2009An enhanced adaptive CUSUM control chart 2010Enhancing the performance of EWMA charts 2011A comparison study of effectiveness and robustness of control charts for monitoring process mean 2012Control charts for location based on different sampling schemes 2007Monitoring process variability using auxiliary information

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2017New EWMA control charts for monitoring process dispersion using auxiliary information 2017New Synthetic CUSUM and Synthetic EWMA Control Charts for Monitoring the Process Mean using Auxiliary Information 2021Neutrosophic Rayleigh Model With Some Basic Characteristics and Engineering Applications 2020On a class of mixed EWMA‐CUSUM median control charts for process monitoring 2018A new adaptive EWMA control chart using auxiliary information for monitoring the process mean

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