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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Change-point estimation of the process fraction non-conforming with a linear trend in statistical process control
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Change-point estimation of the process fraction non-conforming with a linear trend in statistical process control

机译：统计过程控制中不符合线性趋势的过程分数的变化点估计

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摘要

Despite the fact that control charts are able to trigger a signal when a process has changed, it does not indicate when the process change has begun. The time difference between the changing point and a signal of a control chart could cause confusions on the sources of the problems. Knowing the exact time of a process change would help to reduce the time for identification of the special cause. In this article, a model for the change-point problem is first introduced and a maximum-likelihood estimator (MLE) is applied when a linear trend disturbance is present. Then, Monte Carlo simulation is applied in order to evaluate the accuracy and the precision performances of the proposed change-point estimator. Next, the proposed estimator is compared with the MLE of the process fraction nonconforming change point derived under simple step and monotonic changes following signals from a Shewhart np control chart. The results show that the MLE of the process change point designed for the linear trend outperforms the MLE designed for step and monotonic changes when a linear trend disturbance is present.
机译：尽管控制图能够在过程更改时触发信号，但它并不指示过程更改何时开始。更改点和控制图信号之间的时间差可能会导致问题来源混乱。知道过程更改的确切时间将有助于减少识别特殊原因的时间。在本文中，首先介绍了变化点问题的模型，并在存在线性趋势扰动时应用了最大似然估计器（MLE）。然后，应用蒙特卡洛模拟来评估所提出的变化点估计器的准确性和精度性能。接下来，将所提出的估计器与根据Shewhart np控制图的信号在简单步长和单调变化下得出的过程分数不合格变化点的MLE相比较。结果表明，当存在线性趋势扰动时，为线性趋势设计的过程更改点的MLE优于为阶跃和单调变化设计的MLE。

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