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New EWMA Control Charts for Monitoring Mean Under Non-normal Processes Using Repetitive Sampling

  • Nadia Saeed
  • Shahid Kamal
Research Paper

Abstract

Control charts in statistical process control are powerful tools for assessing the process stability. The traditional charts perform well under the assumption of normality, but when data violate the assumption of normality, the robust approaches are needed. The aim of the research is to develop exponentially weighted moving average control charts for mean (EWMAM) based on M-scale estimators with in-control variance under non-normal processes using repetitive sampling scheme. Since M-scale estimators are considered as an alternative to standard deviation, the control charts are developed using these estimators. The performance of proposed charts is compared with the traditional EWMAM chart on the basis of out-of-control average run lengths. The application on practical data set is also provided.

Keywords

Robust Repetitive M-estimators Average run length EWMAM 

Notes

Acknowledgements

The authors are thankful to the editor and reviewers for their valuable comments to improve the quality of this manuscript.

Author Contributions

Ms. NS performed the research and Prof. Dr. SK supervised and contributed editorial input.

Compliance with Ethical Standards

Conflict of interest

The authors declare no conflict of interest regarding the publication of this paper.

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Copyright information

© Shiraz University 2018

Authors and Affiliations

  1. 1.College of Statistical and Actuarial SciencesUniversity of the PunjabLahorePakistan

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