Monitoring Poisson observations using modified exponentially weighted moving average control charts

In certain production processes, it is necessary or more convenient to use counts of defects or conformance per unit of measurement to indicate whether a production process is in control or not. Counts of this kind are often well fitted by a Poisson distribution. Three modified exponentially weighted moving average (EWMA) control charts are developed in this paper for monitoring the Poisson counts. The average run length (ARL) and the probability function of the run length of these modified control charts can be computed exactly using results from the Markov Chain theory. These modified control charts are demonstrated to be generally superior than the Shewhart control chart based on ARL consideration. Tables of in-control ARLs of these modified control charts are given to assist the implementation of these modified control charts. The implementation and design of these EWMA control charts are discussed. The use of these modified EWMA control charts is illustrated with an example.