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Productivity improvement: throughput sensitivity analysis using a single simulation
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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: 1087 - 1094  
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): 5,   Downloads (12 Months): 23,   Citation Count: 1
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ABSTRACT

This paper describes a novel method of calculating the sensitivity of the manufacturing system throughput to the variables of the machines. The sensitivity analysis needs only a single simulation, yet is easy to use and provides accurate results. This sensitivity analysis is then used to predict the change in the system throughput due to a change of the variables of the machines provided that the system change does not significantly change the bottleneck. These predictions can be used for a local optimization, allowing the use of a steepest descent optimization algorithm. The method is based on improving the momentary shifting bottlenecks. The shifting bottlenecks are detected using the shifting bottleneck detection method based on the active duration, i.e., the time a machine is active without interruption. The method is easy to understand and easy to implement in existing simulation software.


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