en و موضوعات مربوط Other Related Subject پژوهشي Research <p> <i> 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 non-normal 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 a significant 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 . </i></p> Linear profile; Non-normality; Autocorrelation; Average run length; Exponentially weighted moving average control chart 221 230 http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-14-2&slc_lang=en&sid=1 Rassoul Noorossana : rassoul@iust.ac.ir 18003194753284600836 18003194753284600836 Yes Rassoul Noorossana, Industrial Engineering Department Islamic Azad University, South-Tehran Branch, Tehran, Iran Abbas Saghaei a.saghaei@srbiau.ac.ir 18003194753284600837 18003194753284600837 No Industrial Engineering Department Islamic Azad University, Science and Research Branch, Tehran, Iran Mehdi Dorri 18003194753284600838 18003194753284600838 No Industrial Engineering Department Islamic Azad University, South-Tehran Branch, Tehran, Iran