Rassoul Noorossana - Industrial Engineering Department Islamic Azad University, South-Tehran Branch, Tehran, Iran
Abbas Saghaei - Industrial Engineering Department Islamic Azad University, Science and Research Branch, Tehran, Iran
Mehdi Dorri - Industrial Engineering Department Islamic Azad University, South-Tehran Branch, Tehran, Iran

In an increasing number of practical situations, the quality of a process or product can be effectively characterized and summarized by a profile. A profile is usually a functional relationship between a response variable and one or more explanatory variables which can be modeled frequently using linear or nonlinear regression models. In this paper, we study the effect of non-normality on profile monitoring in Phase II when within or between autocorrelation is present. Different levels of autocorrelation and skewed and heavy-tailed symmetric nonnormal distributions are used in our study to evaluate the performance of three existing monitoring schemes numerically. Simulation results indicate that the non-normality and autocorrelation can have asignificant effect on the in-control performances of the considered schemes. Results also indicate that the out-of-control performances of the schemes are not very sensitive to low and moderate levels of autocorrelation in moderate and large shifts.

Linear profile; Non-normality; Autocorrelation; Average run length; Exponentially weighted moving average control chart