Western Electric (1956) and Nelson (1984) proposed rule sets to detect visually obvious process upsets on a control chart. Performance evaluation of these rules require simulating situations that correspond to their intended detection purposes such as linear drift, cycling, seesaw and sustained process mean shifts. These non-random process patterns become visually obvious in the presence of reduced variation. Contrary to previous assessments where variance is assumed constant, Western Electric and Nelson rule sets are shown to be preferred over Shewhart X and CUSUM charts for detecting non-random patterns of process mean in the presence of variance reduction over wide ranges of slopes, cycle period/amplitude combinations, alternating shift and sustained shift sizes. One real-data example from Deming's book Out of the Crisis is provided that affirms implications of extensive simulation analyses.

Western Electric (1956) 和 Nelson (1984) 提出了规则集来检测控制图上视觉上明显的过程扰动。这些规则的性能评估需要模拟与其预期检测目的相对应的情况，例如线性漂移、循环、跷跷板和持续过程均值漂移。这些非随机的工艺模式在变化减少的情况下在视觉上变得明显。与之前假设方差为常数的评估相反，Western Electric 和 Nelson 规则集被证明优于 Shewhart X和 CUSUM 图表，用于检测在大范围斜率、周期期间存在方差减少的过程均值的非随机模式/幅度组合，交替移位和持续移位大小。Deming 书中的一个真实数据示例提供了走出危机，肯定了广泛模拟分析的影响。