Maufacturing supply chain applications 1

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Maufacturing supply chain applications 1: capacity and backlog management in queuing-based supply chains

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Winter Simulation Conference archive
Proceedings of the 34th conference on Winter simulation: exploring new frontiers table of contents

San Diego, California

SESSION: Applications in logistics, transportation, and distribution table of contents

Pages: 1302 - 1305

Year of Publication: 2002

ISBN:0-7803-7615-3

Authors

Edward G. Anderson	The University of Texas at Austin, Austin, TX
Douglas J. Morrice	The University of Texas at Austin, Austin, TX

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

Bibliometrics

Downloads (6 Weeks): 1, Downloads (12 Months): 13, Citation Count: 1

Additional Information:

abstract references cited by collaborative colleagues

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ABSTRACT

In this paper, we model and analyze a type of two-stage serial supply chain often found in service sector and make-to-order manufacturing industries. The chain holds no finished goods inventory at either stage. Rather, processing occurs only after an order is received and backlogs are managed solely by adjusting capacity. We model this supply chain using a tandem queuing model. Our analysis considers the impact of changes in first stage lead-time and capacity adjustment time on backlog, waiting time, and capacity variances at both stages. The results can be used to support the argument for better coordination across stages in these types of supply chains.

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.

	1	Anderson, E. G. and D. J. Morrice. 2001. Capacity and Backlog Management in Service-Oriented Supply Chains. Working Paper, The University of Texas at Austin.
	2	Anderson, E. G. and D. J. Morrice. 2000. A Simulation Game for Service-Oriented Supply Chain Management J. of Production Oper. Man.9 40--55.
	3	Edward G. Anderson , Douglas J. Morrice, A simulation model to study the dynamics in a service-oriented supply chain, Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future, p.742-748, December 05-08, 1999, Phoenix, Arizona, United States [doi>10.1145/324138.324470]
	4	Chen, H., P. Yang, D. D. Yao. 1994. Control and Scheduling in a Two-station Queueing Network: Optimal Policies and Heuristics. Queueing Sys.18 301--332.
	5	Fitzsimmons, J. A., and M. J. Fitzsimmons 1998. Service Management: Operations, Strategy, and Information Technology. Boston: Irwin/McGraw-Hill.
	6	Rosberg, Z., P. P. Varaiya, J. C. Walrand. 1982. Optimal Control of Service in Tandem Queues. IEEE Trans. on Auto. Control27 600--610.

CITED BY

Douglas J. Morrice , Edward G. Anderson , Saurav Bharadwaj, A simulation study to assess the efficacy of linear control theory models for the coordination of a two-stage customized service supply chain, Proceedings of the 36th conference on Winter simulation, December 05-08, 2004, Washington, D.C.

Collaborative Colleagues:

Edward G. Anderson: colleagues

Douglas J. Morrice: colleagues

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