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AUXILIARY INFORMATION BASED CONTROL CHARTS FOR MEAN AND VARIABILITY USING RUNS RULES
Keywords:
Average run length, control chart, auxiliary information, runs rules, regression estimatorDOI:
https://doi.org/10.17654/0972361724043Abstract
The control chart is an important statistical tool used to monitor the process parameters. In recent studies, auxiliary information based (AIB) control charts have shown better run length performances than those constructed without using it. The AIB charts are based on plotting statistic that requires information on the study variable and on any correlated auxiliary variable for efficiently monitoring the process parameters. In this paper, we propose an improvement to the performance of the AIB control charts for monitoring the process mean and process variance by making the use of runs rules. The average run length (ARL) performance of the proposed runs rules charts is investigated using simulation study and is compared with the originally proposed control charts based on auxiliary information without runs rules and traditional Shewhart and charts. The proposed runs rules charts are found to be efficient for monitoring the process mean and variance of normally distributed processes mean and process variance by making the use of runs rules. The average run length (ARL) performance of the proposed runs rules charts is investigated using simulation study and is compared with the originally proposed control charts based on auxiliary information without runs rules and traditional Shewhart $\bar{X}$ and $S^2$ charts. The proposed runs rules charts are found to be efficient for monitoring the process mean and variance of normally distributed processes.
Received: January 10, 2024
Accepted: April 12, 2024
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