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Likelihood ratio test-based chart for monitoring the process variability
Authors:Jiujun Zhang  Chuan He  Zhonghua Li
Affiliation:1. Department of Mathematics, Liaoning University, Shenyang, P.R. China;2. Department of Mathematics, Northeastern University, Shenyang, P.R. China;3. Institute of Statistics and LPMC, Nankai University, Tianjin, P.R. China
Abstract:This article proposes a new chart with the generalized likelihood ratio (GLR) test statistics for monitoring the process variance of a normally distributed process. The new chart can be easily designed and constructed and the computation results show that it provides quite a satisfactory performance, including the detection of the decrease in the variance and the individual observation at the sampling point which are very important in many practical applications. Average run length (ARL) comparisons between other procedures and the new chart are presented. The optimal parameters that can be used as a design aid in selecting specific parameter values based on the ARL are described. The application of our proposed method is illustrated by a real data example from chemical process control.
Keywords:Average run length  Exponentially weighted moving average  Likelihood ratio test  Statistical process control
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