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Manufacturing analysis and control: buffer allocation model based on a single simulation
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Proceedings of the 35th conference on Winter simulation: driving innovation table of contents
New Orleans, Louisiana
SESSION: Manufacturing applications table of contents
Pages: 1238 - 1246  
Year of Publication: 2003
ISBN:0-7803-8132-7
Authors
Christoph Roser  TOYOTA Central Research and Development Laboratories Nagakute, Aichi Japan
Masaru Nakano  TOYOTA Central Research and Development Laboratories Nagakute, Aichi Japan
Minoru Tanaka  TOYOTA Central Research and Development Laboratories Nagakute, Aichi Japan
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
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
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
Winter Simulation Conference 
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Downloads (6 Weeks): 2,   Downloads (12 Months): 31,   Citation Count: 2
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ABSTRACT

Allocating buffers in manufacturing systems is one of easiest ways to improve the throughput of the system, as changes can be implemented quickly and the initial cost of the change is low. Yet, while an increase in the buffer size usually increases the throughput, it often also increases the work in progress and the makespan, therefore increasing the inventory and the time to the customer. Subsequently, the trade off between the throughput, the work in progress, and the makespan are of significant research interest. This paper describes a general prediction model of these performance measures for different buffer size increases based on only a single simulation. A fully automated implementation of the simulation analysis and prediction model for manufacturing systems of any size and complexity is available. The method can be used for flow shops, job shops, and serial or parallel systems.


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