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TITLE: CUSUM Schemes for Statistical Monitoring of Queueing Systems
SPEAKER: Dr. Nan Chen, NUS
ABSTRACT:
Queueing Performance Metrics (QPMs) estimate important measures of the system performance, like average cycle time, average waiting length, and throughput rate. These metrics need to be quantitatively evaluated and monitored in real time to continuously improve the system performance. However, QPMs are often highly stochastic, and hence are difficult to monitor using existing methods. In this paper, we propose the cumulative sum (CUSUM) schemes to efficiently monitor the parameters of typical queueing systems. We compared the CUSUM schemes with several alternative methods, and demonstrated that the performance of CUSUM is superior, responding faster to many shift patterns. We also investigate the performance of the CUSUM schemes based on different sampling schemes. We illustrated that more information from complete observations can indeed improve the monitoring performance of CUSUM charts. At last, we used a case study to demonstrate the application of our approach.
Bio: Dr. Nan Chen is an Assistant Professor in the Department of Industrial and Systems Engineering at National University of Singapore. He obtained his B.S. degree in Automation from Tsinghua University, and M.S. degree in Computer Science, M.S. degree in Statistics, and Ph.D. degree in Industrial Engineering from University of Wisconsin-Madison. His research interests include statistical modeling and surveillance of service systems, condition monitoring and prognostics. He is a member of INFORMS, IIE, and IEEE.
