EXTENDED POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE CONTROL CHART FOR MONITORING PROCESS QUALITY

摘要

The c chart is frequently applied to monitor the number of non-conforming products. However, classical c charts are fairly inefficient in detecting small shifts in the nonconformities of process mean when small shifts in the nonconformities of process mean result from assignable causes. Hence, the Poisson exponentially weighted moving average (Poisson EWMA) control scheme is another superior alternative to c charts. This study extends the Poisson EWMA control chart. This generalized chart is referred to herein as the Poisson generally weighted moving average (Poisson GWMA) control chart. This study also presents the Poisson GWMA control chart for monitoring the Poisson counts. Simulation is used to evaluate the average run length (ARL) properties of the c chart, the Poisson EWMA control chart and the Poisson GWMA control chart. The Poisson GWMA control chart is superior to the Poisson EWMA control chart as measured by ARL. An example is also presented to illustrate this study. Significance: This study presents a way to extend the exponentially weighted moving average control chart to the case of Poisson data for fraction nonconforming. Moreover, the developed general model is more flexible and easily implemented, making it attractive and useful to practitioners.