Memory‐Type Control Charts for Monitoring the Process Dispersion |
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Authors: | Nasir Abbas Muhammad Riaz Ronald J. M. M. Does |
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Affiliation: | 1. Department of Statistics, University of Sargodha, , Pakistan;2. Department of Statistics, Quaid‐i‐Azam University Islamabad, , Pakistan;3. Department of Mathematics and Statistics, King Fahad University of Petroleum and Minerals, , Dhahran, 31261 Saudi Arabia;4. Department of Quantitative Economics, IBIS, UvA, University of Amsterdam, , 1018 TV Amsterdam, The Netherlands |
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Abstract: | Control charts have been broadly used for monitoring the process mean and dispersion. Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are memory control charts as they utilize the past information in setting up the control structure. This makes CUSUM and EWMA‐type charts good at detecting small disturbances in the process. This article proposes two new memory control charts for monitoring process dispersion, named as floating T ? S2 and floating U ? S2 control charts, respectively. The average run length (ARL) performance of the proposed charts is evaluated through a simulation study and is also compared with the CUSUM and EWMA charts for process dispersion. It is found that the proposed charts are better in detecting both positive as well as negative shifts. An additional comparison shows that the floating U ? S2 chart has slightly smaller ARLs for larger shifts, while for smaller shifts, the floating T ? S2 chart has better performance. An example is also provided which shows the application of the proposed charts on simulated datasets. Copyright © 2013 John Wiley & Sons, Ltd. |
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Keywords: | average run length control chart Johnson SB transformation logarithmic transformation process variability statistical process control (SPC) |
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