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A practical bottleneck detection method
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Source Winter Simulation Conference archive
Proceedings of the 33nd conference on Winter simulation table of contents
Arlington, Virginia
SESSION: Manufacturing applications table of contents
Pages: 949 - 953  
Year of Publication: 2001
ISBN:0-7803-7309-X
Authors
Christoph Roser  Toyota Central Research and Development Laboratories, Nagakute, Aichi, 480-1192, JAPAN
Masaru Nakano  Toyota Central Research and Development Laboratories, Nagakute, Aichi, 480-1192, JAPAN
Minoru Tanaka  Toyota Central Research and Development Laboratories, Nagakute, Aichi, 480-1192, JAPAN
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
SCS : The Society for Computer Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 36,   Citation Count: 7
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ABSTRACT

This paper describes a novel method for detecting the bottleneck in a discrete event system by examining the average duration of a machine being active for all machines. The machine with the longest average uninterrupted active period is considered the bottleneck. The method is widely applicable and also capable of analyzing complex and sophisticated systems. The results are highly accurate, distinguishing between bottleneck machines and non-bottleneck machines with a high level of confidence. This approach is very easy to use and can be implemented into existing simulation tools with little effort, requiring only an analysis of the log file which is readily available by almost all simulation tools. This method satisfies not only academic requirements with respect to accuracy but also industry requirements with respect to usability.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Blake, Russell P., and Breese, John S. 1995. Automatic Bottleneck Detection. Technical Report MSR-TR-95-10, Microsoft Corporation (Redmond, WA), USA.
 
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Goldratt, Eliyahu M. 1992. The Goal: A Process of Ongoing Improvement. North River Press.
 
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Kubota, Fumiko, Sato, Shuichi, and Nakano, Masaru 1999. Enterprise Modeling and Simulation Platform Integrated Manufacturing System Design and Supply Chain. In IEEE Conference on Systems, Man, and Cybernetics, 511-515, Tokyo, Japan.
 
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Luthi, Johannes, and Haring, Guenter 1997. Bottleneck Analysis for Computer and Communication Systems with Workload Variabilities & Uncertainties. In Proceedings of 2nd International Symposium on Mathematical Modelling, I. Troch and F. Breitenecker, 525-534, Vienna, Austria.
 
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Nakano, Masaru, Sugiura, Norio, Tanaka, Minoru, and Kuno, Toshitaka 1994. ROPSII: Agent Oriented Manufacturing Simulator on the basis of Robot Simulator. In Japan-USA Symposium on Flexible Automation, 201-208, Kobe, Japan.

CITED BY  7
 
 
 
 
 
 
 

Collaborative Colleagues:
Christoph Roser: colleagues
Masaru Nakano: colleagues
Minoru Tanaka: colleagues

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