Abstract
Bottlenecks, the key ingredients for improving the performances of the production networks, have been profoundly studied during the last decade. Yet, because of the complexity of the research results, there is still a significant gap between theory and practice. In this paper, we review various bottleneck definitions, detection methods and the asymptotic results and provide a practical guidance for recognizing and utilizing the bottlenecks in production networks. Queueing theory works as the mathematical foundation in our study. Various definitions of the bottlenecks are classified as either Performance in Processing (PIP) based or sensitivity based definitions, which reflect the preferences of the managers. Detection methods are surveyed closely based on the definitions. These methods are used to recognize the bottlenecks and to provide diagnosis results to managers. Comparisons show that different detection methods may lead to vastly different conclusions. The recognition of the bottlenecks has another advantage: the ultimate phenomena of the bottlenecks can greatly reduce the computation complexity in calculating the system performances. Bottlenecks based approximation and asymptotic results are studied to exhibit the contribution of bottlenecks in performance estimation and theoretical analysis.
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This work was supported by NSFC Grant. No. (60074012,60274011) and NCET-04-0094 program.
Yongcai Wang received the B.S. degree in automatic control from Tsinghua University, Beijing, China, in 2001. He is currently pursuing the Ph.D. degree in the Department of Automation at Tsinghua University. His current research interests include bottleneck analysis in complex network systems, integrated layer design in wireless sensor networks and performance evaluation of parallel and distributed systems.
Qianchuan Zhao received the B.E. degree in automatic control in 1992, and the B.S. degree in applied mathematics and the Ph.D. degree in control theory and its applications from Tsinghua University, Beijing, China, in 1992 and 1996, respectively. Currently, he is a Professor in the Department of Automation at Tsinghua University. He was a Visiting Scholar at Carnegie Mellon University, Pittsburgh, PA, in 2000, and at Harvard University, Cambridge, MA, in 2002. His current research interests include DEDS theory, sensor networks and the optimization of complex systems. He is an associate editor of Journal of Optimization Theory and Applications.
Dazhong Zheng received the diploma in automatic control from Tsinghua University, Beijing, China, in 1959. Currently, he is a Professor in control theory and engineering with the Department of Automatic Control at Tsinghua University, Beijing, China, where he has been since 1959. He was a Visiting Scholar in the Department of Electrical Engineering at the State University of New York at Stony Brook from 1981 to 1983 and from April to November 1993. His research interests include linear systems, discrete event dynamic systems, and power systems. He has published many journal papers and five books. He is also a Deputy Editor-In-Chief of Acta Automatica Sinica, Beijing, China. Currently, he is a Vice-Chairman of control theory technical committee for Chinese Association of Automation (CAA).
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Wang, Y., Zhao, Q. & Zheng, D. Bottlenecks in production networks: An overview. J. Syst. Sci. Syst. Eng. 14, 347–363 (2005). https://doi.org/10.1007/s11518-006-0198-3
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DOI: https://doi.org/10.1007/s11518-006-0198-3