Indirect cycle-time quantile estimation for non-FIFO dispatching policies
Pages 1829 - 1835
Abstract
Previous work has shown that the Cornish-Fisher expansion (CFE) can be used successfully in conjunction with discrete event simulation models of manufacturing systems to estimate cycle-time quantiles. However, the accuracy of the approach degrades when non-FIFO dispatching rules are employed for at least one workstation. This paper suggests a modification to the CFE-only approach which utilizes a power data transformation in conjunction with the CFE. An overview of the suggested approach is given, and results of the implemented approach are presented for a model of a non-volatile memory factory. Cycle-time quantiles for this system are estimated using the CFE with and without the data transformation, and results show a significant accuracy improvement in cycle-time quantile estimation when the transformation is used. Additionally, the technique is shown to be easy to implement, to require very low data storage, and to allow easy estimation of the entire cycle-time cumulative distribution function.
References
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- Indirect cycle-time quantile estimation for non-FIFO dispatching policies
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Published In
December 2006
2429 pages
ISBN:1424405017
- Editors:
- L. Felipe Perrone,
- Barry G. Lawson,
- Jason Liu,
- Frederick P. Wieland,
- General Chair:
- David Nicol,
- Program Chair:
- Richard Fujimoto
Sponsors
- IIE: Institute of Industrial Engineers
- ASA: American Statistical Association
- IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
- IEEE-CS\DATC: The IEEE Computer Society
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- NIST: National Institute of Standards and Technology
- (SCS): The Society for Modeling and Simulation International
- INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation
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Winter Simulation Conference
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Published: 03 December 2006
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- IIE
- ASA
- IEICE ESS
- IEEE-CS\DATC
- SIGSIM
- NIST
- (SCS)
- INFORMS-CS
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WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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