Linear Profile Monitoring in the Presence of Non-Normality and Autocorrelation

• Main Authors: Rassoul Noorossana, Abbas Saghaei, Mehdi Dorri
• Format: Article
• Language: English
• Published: Iran University of Science & Technology 2010-12-01
• Series: International Journal of Industrial Engineering and Production Research
• Subjects: Linear profile; Non-normality; Autocorrelation; Average run length; Exponentially weighted moving average control chart
• Online Access: http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-14-2&slc_lang=en&sid=1

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 .