Abstract

To online monitor the longitudinal performance of processes and give early signals to processes with irregular patterns, a series of dynamic screening systems (DySS) have been proposed in the literature. Existing DySS methods are all based on estimation of the in-control (IC) mean and variance of processes with a regular longitudinal pattern. In this paper, a new DySS method is suggested, which is based on estimation of the IC distribution of processes with a regular longitudinal pattern. Based on the estimated IC distribution, a statistical process control chart is constructed for sequentially detecting any distributional shifts in a longitudinal process. The suggested control chart is relatively simple to design and implement, and it is robust to the true IC distribution. Numerical examples show that it outperforms some representative existing DySS methods. These properties make it an ideal tool for dynamic screening applications, which is demonstrated by a real-data example.

摘要

为了在线监测过程的纵向性能并为具有不规则模式的过程提供早期信号，文献中提出了一系列动态筛选系统 (DySS)。现有的 DySS 方法都基于对具有规则纵向模式的过程的控制 (IC) 均值和方差的估计。在本文中，提出了一种新的 DySS 方法，该方法基于对具有规则纵向模式的工艺的 IC 分布的估计。基于估计的 IC 分布，构建统计过程控制图，用于顺序检测纵向过程中的任何分布偏移。建议的控制图设计和实现相对简单，并且对真实的 IC 分布具有鲁棒性。数值例子表明它优于一些具有代表性的现有 DySS 方法。这些特性使其成为动态筛选应用的理想工具，真实数据示例证明了这一点。