**1. Introduction**

The traditional methodology of Statistical Quality Control (SEQ) is based on a fundamental supposition that the process of the data is independent statisticaly, however, the data not al‐ ways are independent. When a process follows an adaptable model, or when the process is a deterministic function, the data will be autocorrelated.

Drawing the process of data is extremely valuable, however, under such circumstances, there isn't any scientific reason to use the traditional techniques of statistical control of quality, be‐ cause it will induce erroneous conclusions and facilitate a safety absence that the process is under statistical control with flaw in the identification of systematic variation of the process.

Thus, the theme here proposed is to investigate the acting and the adaptation of the tradi‐ tional use of the statistical control of process methods in no-stationary processes, and to dis‐ cuss the use of time series methodologies to work with correlated observations.
