Change-Point Estimation in the Mean of a Two-Attribute Attribute Process with a Binomial Distribution

Document Type : Original Article

Authors

1 .Islamic Azad University, South Tehran Branch, Iran

2 Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran.

Abstract
Control charts are powerful tools used for monitoring process variations. In statistical process control, there are many situations in which qualitative (attribute) characteristics of a product or process are monitored simultaneously. Although an out-of-control signal in control charts indicates the presence of a process change, the exact time at which the change occurs is often unknown. Identifying the precise change-point helps process engineers determine the causes of variation and improve the process.
In this study, statistical process control techniques are examined for a process in which qualitative attribute characteristics of the conforming/nonconforming type are measured in a bivariate form. Using the maximum likelihood method, we propose an estimator for determining the change-point in such processes. It is assumed that the two qualitative attribute characteristics in a product are correlated. Simulation results show that the proposed method performs well in detecting the change-point in the process mean vector.





 




 

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