The control chart is the most important tool in the statistical process control to monitor the industrial process. The additional supporting information related to the underlying quality characteristic increases the sensitivity of the control chart. In this article, auxiliary information-based double moving average $(\text{ADMA})$ control chart is proposed for effective monitoring of the process mean. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. The run-length profiles of the $\text{ADMA}$ control chart are calculated using the Monto Carlo simulation. The performance of the $\text{ADMA}$ chart is compared with its memory-type counterparts. The numerical simulation study shows that the proposed $\text{ADMA}$ charting structure performs uniformly better than the competitors in the terms of average run length and other run length characteristics. Two illustrative examples related to real datasets and a third from simulated datasets are also provided to implement the proposal.

控制图是统计过程控制中监控工业过程的最重要的工具。与基础质量特性相关的附加支持信息增加了控制图的敏感性。在本文中，基于辅助信息的双移动平均线$(\text{ADMA})$提出控制图以有效监控过程均值。辅助变量和支持变量形式的回归估计提供了过程变量均值的无偏且有效的统计量。的运行长度配置文件$\text{ADMA}$控制图是使用蒙托卡罗模拟计算的。的表现$\text{ADMA}$图表与其内存类型的对应物进行了比较。数值模拟研究表明，所提出的$\text{ADMA}$图表结构在平均游程长度和其他游程长度特征方面的表现均优于竞争对手。还提供了与真实数据集相关的两个说明性示例和来自模拟数据集的第三个示例以实施该提案。