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An Exponentially Weighted Moving Average Control Chart for Bernoulli Data

机译:伯努利数据的指数加权移动平均控制图

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We consider a production process in which units are produced in a sequential manner. The units can,,for example, be manufactured items or services, provided to clients. Each unit produced can be a failure with probability p or a success (non-failure) with probability (1-p). A novel exponentially weighted moving average (EWMA) control chart intended for surveillance of the probability of failure, p, is described. The chart is based on counting the number of non-failures produced between failures in combination with a variance-stabilizing transformation. The distribution function of the transformation is given and its limit for small values of p is derived. Control of high yield processes is discussed and the chart is shown to perform very well in comparison with both the most common alternative EWMA chart and the CUSUM chart. The construction and the use of the proposed EWMA chart are described and a practical example is given. It is demonstrated how the method communicates the current failure probability in a direct and interpretable way, which makes it well suited for surveillance of a great variety of activities in industry or in the service sector such as in hospitals, for example.
机译:我们考虑一种生产过程,在该过程中按顺序生产单元。这些单元可以是例如提供给客户的制造项目或服务。产生的每个单位可以是概率为p的失败或概率为(1-p)的成功(非失败)。描述了一种新颖的指数加权移动平均(EWMA)控制图,旨在监控故障概率p。该图表是基于对两次故障之间产生的非故障数量以及方差稳定化转换的计数。给出了变换的分布函数,并得出了其对p较小值的限制。讨论了高产量过程的控制,并且该图表与最常见的替代EWMA图表和CUSUM图表相比,具有很好的性能。描述了所提出的EWMA图的构造和使用,并给出了一个实际示例。演示了该方法如何以直接且可解释的方式传达当前故障概率,这使其非常适合监视工业或服务部门(例如医院)中的各种活动。

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