An Adaptive CUSUM Procedure for Signaling Process Variance Changes of Unknown Sizes

Abstract

Similar to the CUSUM location chart, the traditional CUSUM dispersion chart can be designed to optimize the detection of specified variance changes. However, this optimality property requires that the magnitude of the out-of-control variance is known exactly a priori. To get away from this requirement, this paper suggests an adaptive CUSUM procedure for signaling changes in the process variance of unknown sizes. The basic idea is to first estimate the current process variance and then dynamically adjust the CUSUM chart to match the variance estimate. A two-dimensional Markov chain model is developed to analyze the chart performance. The comparison results with the traditional CUSUM dispersion chart and other competitive procedures favor the proposed one.

• Change-Point Detection
• Dispersion Chart
• Markov Chain
• Statistical Process Control

Additional information

Notes on contributors

Lianjie Shu

Dr. Shu is an Associate Professor in the Faculty of Business Administration. His email address is [email protected].

Hang-Fai Yeung

Dr. Yeung is an Assistant Professor in the Faculty of Business Administration. His email address is [email protected].

Wei Jiang

Dr. Jiang is a visiting Associate Professor in Department of Industrial Engineering & Logistics Management. His email address is [email protected].