In many industrial manufacturing processes, the quality of products depends on the relation between two main ingredients or characteristics. Often, this calls for monitoring the ratio of two normal random variables with statistical process control (SPC) techniques. A large number of studies related to designing control charts monitoring this ratio have been published. However, these studies are based purely on the assumption of independent observations. In practice, autocorrelation between observations can exist and should be modeled to protect against the false alarm rate inflation when implementing a control chart. In this paper, we tackle this problem by investigating the performance of the Shewhart control chart monitoring the ratio of two normal variables, (denoted as Shewhart-RZ), in the presence of autocorrelation between successive observations. The autocorrelation is modeled through the bivariate autoregressive model VAR(1). We also provide an example to illustrates the use of the Shewhart-RZ control chart on a quality control problem.
翻译:在许多工业制造过程中,产品的质量取决于两个主要成份或特性之间的关系。这往往要求用统计过程控制技术来监测两个正常随机变数的比率。大量与设计监测这一比率的控制图有关的研究已经公布。然而,这些研究完全基于独立观察的假设。在实践中,观测之间的自动联系可以存在,而且应该以模型形式来保护,在使用控制图时,防止虚假的警报率膨胀。在本文件中,我们通过调查 Shewhart控制图的性能来解决这个问题,监测两个正常变数的比率(称为Shewhart-RZ),同时发现连续观测之间的自动关系。自动反向模型VAR(1)建模了自动反向模型。我们还提供了一个例子,说明在质量控制问题上使用 Shewhart-RZ控制图的情况。