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Approximate distribution of demerit statistic—A bounding approach

机译:劣势统计量的近似分布-一种边界方法

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摘要

The traditional classical demerit control chart is used to plot the demerit statistic, a weighted sum of the number of defects in each category, on a control chart. The approximate normal method is usually used to obtain control limits though the distribution that depends on the values of the weights and the parameters of the Poisson distribution which may not always be normal. [Jones, L.A., Woodall, W.H., Conerly, M.D., 1999. Exact properties of demerit control charts. Journal of Quality Technology 31 (2), 207–216] used the characteristic function approach to determine the distribution of the demerit statistic. Unfortunately, the process that they used to determine the distribution needs complex integral evaluation via mathematical software packages or using the approximate truncated infinite series. Moreover, the characteristic function does not provide an accurate result easily. In this paper, a bounding approach is proposed to determine the approximate distribution of the demerit statistic. It is easy to implement and also the approximate error can be controlled to meet the desired accuracy. In addition, an example is demonstrated to illustrate the proposed method. The results indicate that the proposed approach is efficient and accurate. Finally, the performance among the approximate normal method, the characteristic function approach, and the proposed bounding approach are discussed.
机译:传统的经典缺陷控制图用于在控制图上绘制缺陷统计量,即每个类别中缺陷数量的加权总和。尽管权重的分布和泊松分布的参数可能并不总是正态的,但通常使用近似正态方法来获得控制极限。 [Jones,L.A.,Woodall,W.H.,Conerly,M.D.,1999。质量技术杂志31(2),207–216]使用特征函数方法来确定扣分统计的分布。不幸的是,他们用来确定分布的过程需要通过数学软件包或使用近似的无穷大序列进行复杂的积分评估。而且,特征函数不容易提供准确的结果。本文提出了一种边界方法来确定劣势统计量的近似分布。它易于实现,并且可以控制近似误差以满足所需的精度。另外,通过一个例子说明了所提出的方法。结果表明,该方法是有效和准确的。最后,讨论了近似法线法,特征函数法和提出的边界法之间的性能。

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