In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. In this study, auxiliary information‐based moving average (AB‐MA) control chart is designed for efficient monitoring of shifts in the process location parameter. The performance of the AB‐MA control chart is evaluated and compared with existing charts using average run length and other run length characteristics. The comparison reveals that the AB‐MA control chart outperforms the competitors in detecting the small and medium changes in the process location parameter. The application of the proposal is also provided to implement it in real situation.

中文翻译：

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使用辅助变量提高移动平均线控制图的敏感性

在统计过程控制中，用于监视行业制造过程的最有用的工具是控制图。质量从业人员始终希望使用图表结构来标识监视过程中的可持续变化。当引入有关研究变量的其他相关辅助信息时，可提高控制图的灵敏度。辅助变量和支持变量形式的回归估计值提供了过程变量平均值的无偏和有效统计量。在本研究中，基于辅助信息的移动平均（AB-MA）控制图旨在有效监视过程位置参数的变化。评估AB‐MA控制图的性能，并使用平均游程长度和其他游程长度特征将其与现有图表进行比较。比较表明，在检测过程位置参数的中小变化方面，AB-MA控制图的性能优于竞争对手。还提供了该提案的应用程序，以便在实际情况下实施该提案。