International Journal of Industrial Engineering and Production Research (Dec 2010)

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

  • Rassoul Noorossana,
  • Abbas Saghaei,
  • Mehdi Dorri

Journal volume & issue
Vol. 21, no. 4
pp. 221 – 230

Abstract

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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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