Identifying the change time of multivariate binomial processes for step changes and drifts

Subject Areas : Mathematical Optimization

Seyed Taghi Akhavan Niaki ¹ , Majid Khedmati ²

1 - Department of Industrial Engineering, Sharif University of Technology, P.O. Box 11155–9414, Azaadi Ave., Tehran, 1458889694, Iran
2 - Department of Industrial Engineering, Sharif University of Technology, P.O. Box 11155–9414, Azaadi Ave., Tehran, 1458889694, Iran

Received: 2020-10-02 Accepted : 2020-10-02 Published : 2013-12-01

Keywords: Maximum Likelihood Estimator, Multi-binomial processes, Multi-attribute processes, Step change, Linear-trend disturbance, Root/power transformation,

Abstract :

In this paper, a new control chart to monitor multi-binomial processes is first proposed based on a transformation method. Then, the maximum likelihood estimators of change points designed for both step changes and linear-trend disturbances are derived. At the end, the performances of the proposed change-point estimators are evaluated and are compared using some Monte Carlo simulation experiments, considering that the real change type presented in a process are of either a step change or a linear-trend disturbance. According to the results obtained, the change-point estimator designed for step changes outperforms the change-point estimator designed for linear-trend disturbances, when the real change type is a step change. In contrast, the change-point estimator designed for linear-trend disturbances outperforms the change-point estimator designed for step changes, when the real change type is a linear-trend disturbance.