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A multivariate CUSUM control chart for monitoring Gumbel's bivariate exponential data

机译:用于监控Gumbel的双变量指数数据的多变量CUSUM控制图

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Exponentially distributed data are commonly encountered in high-quality processes. Control charts dedicated to the univariate exponential distribution have been extensively studied by many researchers. In this paper, we investigate a multivariate cumulative sum (MCUSUM) control chart for monitoring Gumbel's bivariate exponential (GBE) data. Some tables are provided to determine the optimal design parameters of the proposed MCUSUM GBE chart. Furthermore, both zero-state and steady-state properties of the proposed MCUSUM GBE chart for the raw and the transformed GBE data are compared with the multivariate exponentially weighted moving average (MEWMA) chart and the paired individual cumulative sum (CUSUM) chart. The results show that the proposed MCUSUM GBE chart outperforms the other two types of control charts for most shift domains. In addition, an extension to Gumbel's multivariate exponential (GME) distribution is also investigated. Finally, an illustrative example is provided in order to explain how the proposed MCUSUM GBE chart can be implemented in practice.
机译:指数分布式数据通常在高质量过程中遇到。许多研究人员已经广泛研究了专用于单变量指数分布的控制图。在本文中,我们调查了监控Gumbel的双变量指数(GBE)数据的多变量累积量(MCUSUM)控制图。提供了一些表以确定所提出的MCUSUM GBE图表的最佳设计参数。此外,将所提出的MCUSUM GBE图表的零状态和稳态属性与RAW和变换的GBE数据的多变量指数加权移动平均(MEWMA)图表和配对的各个累积和(CUSUM)图表进行了比较。结果表明,所提出的MCUSUM GBE图表优于大多数换档域的其他两种控制图表。此外,还研究了Gumbel的多变量指数(GME)分布的延伸。最后,提供了说明性示例,以便解释如何在实践中实现所提出的MCUSUM图表。

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