Implementation Issues of Time‐series Based Statistical Process Control

Underlying standard control‐chart methodology is the assumption of independent and identically distributed (IID) random variables. However, autocorrelation and other time‐series effects frequently occur in manufacturing and service quality applications. As a result, it has been suggested that standard methods be extended by using time‐series modeling. A little statistical analysis can go a long way, especially when time‐series effects are strong enough to frustrate efforts directed toward discovery of special causes. But a practical limitation on the use of time‐series modeling is that its implementation requires some sophisticated statistical skills, whereas standard control charts require only elementary statistical knowledge. The choice raises the questions of management philosophy, statistical techniques, and computation.