The Poisson distribution assumption often arises in several industrial applications for modeling defects or nonconformities. In this work, we investigate the one- and two-sided performance of a new adaptive EWMA (exponentially weighted moving average)-type chart for monitoring Poisson count data. An appropriate discrete-state Markov chain technique is provided to compute the exact ARL (average run length) properties. Moreover, comparative studies are conducted to demonstrate the higher sensitivity of the proposed chart in the detection of shifts with various magnitudes. Advices on how to select the appropriate chart parameters are provided and an illustrative numerical example is proposed.

中文翻译：

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用于监测泊松计数数据的最优单边和双边自适应 EWMA 方案

泊松分布假设经常出现在一些用于对缺陷或不合格进行建模的工业应用中。在这项工作中，我们研究了用于监控泊松计数数据的新自适应 EWMA（指数加权移动平均）型图表的单边和双边性能。提供了一种适当的离散状态马尔可夫链技术来计算精确的ARL（平均游程长度）属性。此外，还进行了比较研究，以证明所提出的图表在检测各种幅度的偏移方面具有更高的灵敏度。提供了有关如何选择合适的图表参数的建议，并提出了一个说明性的数值示例。