A Flexible and Generalized Exponentially Weighted Moving Average Control Chart for Count Data

摘要

The Conway-Maxwell-Poisson distribution can be used to model under-dispersed or over-dispersed count data. This study proposes a flexible and generalized attribute exponentially weighted moving average (EWMA), namely GEWMA, control chart for monitoring count data. The proposed EWMA chart is based on the Conway-Maxwell-Poisson distribution. The performance of the proposed chart is evaluated in terms of run length (RL) characteristics such as average RL, median RL, and standard deviation of the RL distribution. The average RL of the proposed GEWMA chart is compared with Sellers chart. The sensitivity of the standard Poisson EWMA (PEWMA) chart is also studied and compared with the proposed GEWMA chart for under-dispersed or over-dispersed data. It has been observed that the PEWMA chart is very sensitive for under-dispersed or over-dispersed data while the proposed GEWMA is very robust. Finally, the generalization of the proposed chart to the Bernoulli EWMA, PEWMA, and geometric EWMA charts is also studied using someone simulated data sets.