Abstract
Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart’s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.
Highlights
In every industrial environment, product quality is affected by the variation in the manufacturing process
Inspired by Huwang et al [10] and Abbas [14], we suggest a one-sided homogeneously weighted moving average (HWMA) chart to monitor the changes in the increase of the process variance, hereafter labeled as SJH
We have suggested the SJH chart for quickly and efficiently monitoring the changes in the upward increase of the process variance
Summary
Product quality is affected by the variation in the manufacturing process. The work of Reference [10] suggested the one-sided EWMA chart to monitor the increase in the process variance and labeled this chart as the H-EWMA chart. Motivated by Reference [11], the authors of Reference [13] introduced a mixture of generally weighted moving average (GWMA) and CUSUM charts for monitoring small deviations in the process variance. To enhance the HWMA chart’s performance, a double HWMA chart for efficient monitoring of the process mean was suggested in Reference [18]. Inspired by Huwang et al [10] and Abbas [14], we suggest a one-sided HWMA chart to monitor the changes in the increase of the process variance, hereafter labeled as SJH.
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