Time-Series Modeling for Statistical Process Control
指出实际生产过程中数据常存在自相关等时间序列效应，导致标准控制图失效；提出先对时间序列效应建模并拟合，再对残差应用控制图，同时单独绘制拟合值以展示系统效应。
In statistical process control, a state of statistical control is identified with a process generating independent and identically distributed random variables. It is often difficult in practice to attain a state of statistical control in this strict sense; autocorrelations and other systematic time-series effects are often substantial. In the face of these effects, standard control-chart procedures can be seriously misleading. We propose and illustrate statistical modeling and fitting of time-series effects and the application of standard control-chart procedures to the residuals from these fits. The fitted values can be plotted separately to show estimates of the systematic effects.