On Dual Use of Auxiliary Information for Efficient Monitoring

Saddam Akber Abbasi · Muhammad Riaz

48 citations0/0 files storedQuality and Reliability Engineering International

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

Abstract

In this study, a new idea has been proposed in statistical process control by making dual use of auxiliary information, that is, for ranking as well as at the estimation stage. The control charts are proposed based on regression estimator in three basic ranked set schemes, that is, ranked-set sampling (RSS), median RSS, and extreme RSS. The power of detection is used as a performance measure for evaluation and comparison of control charts. Comparisons revealed that the newly proposed charts (making dual use of auxiliary information) performed significantly better compared with the existing location charts. An illustrative example is also provided for the application of the proposed charts. Copyright © 2015 John Wiley & Sons, Ltd.

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References

1954CONTINUOUS INSPECTION SCHEMES 1959Control Chart Tests Based on Geometric Moving Averages 2007Introduction to Statistical Quality Control 2003Statistical quality control based on ranked set sampling 2004Quality Control Chart for the Mean using Double Ranked Set Sampling 2011On Proper Choice of Variability Control Chart for Normal and Non‐normal Processes 2012Control charts for location based on different sampling schemes 1997Robust Estimation of the Process Standard Deviation for Control Charts

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2017A new double sampling control chart for monitoring process mean using auxiliary information 2017A New Maximum EWMA Control Chart for Simultaneously Monitoring Process Mean and Dispersion Using Auxiliary Information 2015On Effective Dual Use of Auxiliary Information in Variability Control Charts 2018A new Max-HEWMA control chart using auxiliary information 2018A variable sample size and sampling interval control chart for monitoring the process mean using auxiliary information

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