Monitoring process data with seasonal time series model

追蹤季節性時間數列模型之流程資料Control charts are designed and evaluated under the assumption that the observations from the process are independent and identically distributed. However, the independence assumption is often violated in practice. Autocorrelation may be represented in many processes. To solve this problem, it is becoming more common to obtain profiles at each time period. Profile monitoring is the use of control charts for cases in which the quality of a process or product can be characterized by a functional relationship between a response variable and one or more explanatory variables. For the data with seasonal time series model, we propose several monitoring approaches to detect the out-of-control profiles. After considering both Phase I and Phase II schemes, a real example is given to illustrate the results