Authors: Honghao Zhao; Lianjie Shu; Wei Jiang; Kwok-Leung Tsui
Addresses: School of Business, Macau University of Science and Technology, Taipa, Macau, China ' Faculty of Business Administration, University of Macau, Taipa, Macau, China ' Antai College of Economics and Management, Shanghai Jiaotong University, Shanghai, China ' Department of Systems Engineering and Engineering Management, City University of Hong Kong, Hong Kong, China
Abstract: The CUSUM control chart is an effective tool for monitoring both variable and count data. However, it often requires the assumption of known process parameters. To get away from this assumption, the adaptive CUSUM (ACUSUM) procedure has been suggested, with primary focus on the monitoring of variable data. This paper extends the idea of ACUSUM control charts from the monitoring of variable data to the monitoring of count data based on an inhomogeneous Poisson model. The study is motivated by a real example of male thyroid cancer data in New Mexico. The comparison results show that the ACUSUM method generally performs better than the traditional Poisson CUSUM charts and other variations for monitoring a wide range of shifts in the Poisson mean. [Received 11 January 2014; Revised 15 July 2014; Accepted 25 August 2014]
Keywords: adaptive CUSUM; ACUSUM charts; conditional expected delay; inhomogeneous Poisson process; weighted CUSUM; WCUSUM; control charts; variable data monitoring; male thyroid cancer data; statistical process control; SPC.
European Journal of Industrial Engineering, 2015 Vol.9 No.5, pp.692 - 715
Available online: 18 Sep 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article