Control Charts for Poisson Count Data with Varying Sample Sizes

• Published in: Journal of quality technology Vol. 42; no. 3; pp. 260 - 275
• Main Authors: Ryan, Anne G., Woodall, William H.
• Format: Journal Article
• Language: English
• Published: Milwaukee, WI Taylor & Francis 01.07.2010; American Society for Quality; Taylor & Francis Ltd
• Subjects: Applied sciences; Average Run Length; Charts; Control charts; Counting; Cumulative Sum Chart; CUSUM charts; Exact sciences and technology; Exponentially Weighted Moving Average Chart; False alarms; Inventory control, production control. Distribution; Mathematical analysis; Methods; Monitoring; Monitors; Operational research and scientific management; Operational research. Management science; Performance evaluation; Poisson distribution; Process controls; Random variables; Sample size; Simulation; Statistical Process Control; Studies; Statistical process control; Control chart; Sample size; Moving average; Average run length; Likelihood ratio; Mean estimation; Poisson process; Steady state; Exponentially Weighted Moving Average Chart; Weighting; Surveillance; CUSUM method; Cumulative Sum Chart; Monitoring

Various cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts have been recommended to monitor a process with Poisson count data when the sample size varies. We evaluate the ability of these CUSUM and EWMA methods in detecting increases in the Poisson rate by calcula...