Volume 21, Number 4 (IJIEPR 2010)                   IJIEPR 2010, 21(4): 221-230 | Back to browse issues page


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Noorossana R, Saghaei A, Dorri M. Linear Profile Monitoring in the Presence of Non-Normality and Autocorrelation. IJIEPR. 2010; 21 (4) :221-230
URL: http://ijiepr.iust.ac.ir/article-1-239-en.html

Rassoul Noorossana, Industrial Engineering Department Islamic Azad University, South-Tehran Branch, Tehran, Iran , : rassoul@iust.ac.ir
Abstract:   (54507 Views)

  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 .

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Type of Study: Research | Subject: Other Related Subject
Received: 2011/05/3

Cited by [1] [PDF 95 KB]  (120 Download)
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