The process monitoring and construction of control charts involves the measurement of the quality characteristic under certain time and cost constraints. Ranked set sampling (RSS) is a very useful and inexpensive method of obtaining a more representative sample when the actual quantification of sampling units is expensive or destructive, while the ranking of the observations is easier. In this paper, RSS and its variation, extreme RSS, median RSS and neoteric RSS are employed to construct new memory type homogeneously weighted moving average (HWMA) control charts to monitor the process location. The HWMA chart assigns a particular weight to the most recent sample, while all the previous samples are assigned an equal proportion of the remaining weight. The run length properties of the proposed control charts are studied by using extensive Monte Carlo simulations. The performance of the proposed charts is compared with the simple random sampling-based exponentially weighted moving average (EWMA) and HWMA besides RSS-based EWMA counterparts. The comprehensive comparisons established the better shift detection ability of the proposed control charts. To demonstrate the practical implementation of the proposed charts, a real industrial dataset is used which also confirms the better mean shift detection ability of the proposed charts.

过程监控和控制图的构建涉及在一定时间和成本约束下对质量特性的测量。当采样单位的实际量化价格昂贵或具有破坏​​性时，排序集采样（RSS）是一种非常有用且廉价的获取更具代表性的样本的方法，而对观察值的排序则更为容易。本文采用RSS及其变种，极限RSS，中值RSS和新式RSS来构造新的内存类型均匀加权移动平均值（HWMA）控制图来监视过程位置。HWMA图表为最近的样本分配了特定的权重，而所有之前的样本均分配了相等权重的剩余权重。通过使用广泛的蒙特卡洛模拟研究了所提出的控制图的行程特性。所提出的图表的性能与基于RSS的EWMA相比，与基于简单随机抽样的指数加权移动平均值（EWMA）和HWMA进行了比较。综合比较确定了所提出的控制图的更好的换档检测能力。为了演示所提出的图表的实际实现，使用了真实的工业数据集，这也证实了所提出图表的更好的均值漂移检测能力。综合比较确定了所提出的控制图的更好的换档检测能力。为了演示所建议图表的实际实现，使用了真实的工业数据集，这也证实了所建议图表的更好的均值漂移检测能力。综合比较确定了所提出的控制图的更好的换档检测能力。为了演示所建议图表的实际实现，使用了真实的工业数据集，这也证实了所建议图表的更好的均值漂移检测能力。