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Control charts for variables to monitor the process mean and dispersion: a literature review

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  • D.R. Prajapati
  • P.B. Mahapatra

Abstract

It has been concluded that 100% inspection cannot be relied upon to sort out non-conforming products from a product stream. So researchers have suggested to design suitable statistical tools e.g., control charts, which can be used to control the process of manufacturing. A control chart defines a statistic and some criteria such that the probability of statistic meeting the criteria is high when the process is under control and low when the process is out of control. Shewhart (1931) proposed first general model of control charts for variables. Since then, various approaches and their applications have been developed in this area. This paper provides a survey and brief summary of the work on the control charts for variables to monitor the process mean and dispersion from 1931 to 2008.

Suggested Citation

  • D.R. Prajapati & P.B. Mahapatra, 2009. "Control charts for variables to monitor the process mean and dispersion: a literature review," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 4(4), pages 476-520.
    • Handle: RePEc:ids:ijpqma:v:4:y:2009:i:4:p:476-520
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    Cited by:

    1. Azam Moraditadi & Soroush Avakhdarestani, 2016. "Development of fuzzy individual x and moving range control chart," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 17(1), pages 82-103.
    2. Ambreen Shafqat & Muhammad Aslam & Mohammed Albassam, 2020. "Moving Average control charts for Burr X and Inverse Gaussian distributions," Operations Research and Decisions, Wroclaw University of Science Technology, Faculty of Management, vol. 30(4), pages 81-94.

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