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Productivity improvement: shifting bottleneck detection
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Source Winter Simulation Conference archive
Proceedings of the 34th conference on Winter simulation: exploring new frontiers table of contents
San Diego, California
SESSION: Manufacturing applications table of contents
Pages: 1079 - 1086  
Year of Publication: 2002
ISBN:0-7803-7615-3
Authors
Christoph Roser  Software Science Laboratory, Nagakute, Aichi, Japan
Masaru Nakano  Software Science Laboratory, Nagakute, Aichi, Japan
Minoru Tanaka  Software Science Laboratory, Nagakute, Aichi, Japan
Sponsors
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
ACM: Association for Computing Machinery
(SCS) : The Society for Modeling and Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
Publisher
Winter Simulation Conference 
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Downloads (6 Weeks): 8,   Downloads (12 Months): 57,   Citation Count: 8
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ABSTRACT

This paper provides a novel method for detecting bottlenecks in manufacturing systems and the shifting of these bottlenecks. All manufacturing systems are constrained by one or more bottlenecks. Improving the bottleneck will improve the whole system. Yet, finding the bottleneck is no trivial task. Furthermore, the system may change over time or due to random events, and subsequently the bottleneck may shift from one machine to another machine. The shifting bottleneck detection method determines the bottleneck based on the duration a machine is active without interruption. The method is very robust, easy to apply and able to detect the primary and secondary bottlenecks in a wide range of production systems. This allows the use of simulation to predict bottlenecks for both steady state and variable systems. The measurement of the likelihood of a machine being the bottleneck aids in the decision-making regarding the allocation of the available resources.


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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CITED BY  8
Collaborative Colleagues:
Christoph Roser: colleagues
Masaru Nakano: colleagues
Minoru Tanaka: colleagues