IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v53y2007i6p991-1004.html
   My bibliography  Save this article

Performance Bounds for Flexible Systems Requiring Setups

Author

Listed:
  • Mahender P. Singh

    (MIT Center for Transportation and Logistics, Massachusetts Institute of Technology, Room E40-363, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139)

  • Mandyam M. Srinivasan

    (College of Business Administration, The University of Tennessee, 611 Stokely Management Center, Knoxville, Tennessee 37996)

Abstract

Many organizations use product variety as one possible strategy for increasing their competitiveness. They have installed flexible manufacturing systems because these systems offer a powerful means for accommodating production and assembly of a variety of products. However, increased product variety comes at a cost. For instance, if the resource requires to be set up each time it switches to operate on a new product, the resulting delays and costs could negate the intended benefits of increased product variety. Analyzing these flexible resources for optimal design and operation is therefore very important. To address such issues, we model a flexible resource, serving multiple products, using a queueing model--more precisely, a polling model. In this model, a single server attends to multiple service centers (queues) at which requests arrive and queue up for service, performing a setup at a polled queue only if that queue is nonempty. This is the state dependent (SD) polling model. Exact analysis of the SD polling model is inherently very complex. This paper presents a very efficient procedure to compute a hierarchy of successively improving bounds on the values of performance measures obtained from the SD polling model with the exact solution as its limit. This procedure can be applied to quickly estimate performance measures for large SD polling models previously deemed analytically intractable.

Suggested Citation

  • Mahender P. Singh & Mandyam M. Srinivasan, 2007. "Performance Bounds for Flexible Systems Requiring Setups," Management Science, INFORMS, vol. 53(6), pages 991-1004, June.
    • Handle: RePEc:inm:ormnsc:v:53:y:2007:i:6:p:991-1004
    DOI: 10.1287/mnsc.1060.0639
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1060.0639
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.1060.0639?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mandyam M. Srinivasan, 1991. "Nondeterministic Polling Systems," Management Science, INFORMS, vol. 37(6), pages 667-681, June.
    2. Debashish Sarkar & Willard I. Zangwill, 1991. "Variance Effects in Cyclic Production Systems," Management Science, INFORMS, vol. 37(4), pages 444-453, April.
    3. Altman, E. & Blanc, J.P.C. & Khamisy, A. & Yechiali, U., 1994. "Gated-type polling systems with walking and switch-in times," Other publications TiSEM c093d92a-422f-4216-b528-0, Tilburg University, School of Economics and Management.
    4. Leonard Kleinrock & Hanoch Levy, 1988. "The Analysis of Random Polling Systems," Operations Research, INFORMS, vol. 36(5), pages 716-732, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tetsuji Hirayama, 2012. "Analysis of multiclass Markovian polling systems with feedback and composite scheduling algorithms," Annals of Operations Research, Springer, vol. 198(1), pages 83-123, September.
    2. Dieter Fiems & Eitan Altman, 2012. "Gated polling with stationary ergodic walking times, Markovian routing and random feedback," Annals of Operations Research, Springer, vol. 198(1), pages 145-164, September.
    3. Bertsimas, Dimitris., 1995. "The achievable region method in the optimal control of queueing systems : formulations, bounds and policies," Working papers 3837-95., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    4. Samaddar, Subhashish, 2001. "The effect of setup time reduction on its variance," Omega, Elsevier, vol. 29(3), pages 243-247, June.
    5. Rappold, James A. & Yoho, Keenan D., 2014. "Setting safety stocks for stable rotation cycle schedules," International Journal of Production Economics, Elsevier, vol. 156(C), pages 146-158.
    6. Herwig Bruneel & Arnaud Devos, 2024. "Explicit Solutions for Coupled Parallel Queues," Mathematics, MDPI, vol. 12(15), pages 1-31, July.
    7. Robert B. Cooper & Shun-Chen Niu & Mandyam M. Srinivasan, 1998. "When Does Forced Idle Time Improve Performance in Polling Models?," Management Science, INFORMS, vol. 44(8), pages 1079-1086, August.
    8. David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
    9. Subhashish Samaddar & Thomas Whalen, 2008. "Improving Performance in Cyclic Production Systems by Using Forced Variable Idle Setup Time," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 173-180, August.
    10. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    11. Steven J. Erlebacher & Medini R. Singh, 1999. "Optimal Variance Structures and Performance Improvement of Synchronous Assembly Lines," Operations Research, INFORMS, vol. 47(4), pages 601-618, August.
    12. Li, Bo & Arreola-Risa, Antonio, 2017. "Financial risk, inventory decision and process improvement for a firm with random capacity," European Journal of Operational Research, Elsevier, vol. 260(1), pages 183-194.
    13. Dimitris Bertsimas & José Niño-Mora, 1996. "Optimization of multiclass queueing networks with changeover times via the achievable region approach: Part I, the single-station case," Economics Working Papers 302, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 1998.
    14. Samaddar, Subhashish & Hill, Craig A., 2007. "Controlling adverse effect on work in process inventory while reducing machine setup time," European Journal of Operational Research, Elsevier, vol. 180(1), pages 249-261, July.
    15. Germs, Remco & Van Foreest, Nicky D., 2011. "Admission policies for the customized stochastic lot scheduling problem with strict due-dates," European Journal of Operational Research, Elsevier, vol. 213(2), pages 375-383, September.
    16. Jodlbauer, Herbert & Reitner, Sonja, 2012. "Optimizing service-level and relevant cost for a stochastic multi-item cyclic production system," International Journal of Production Economics, Elsevier, vol. 136(2), pages 306-317.
    17. Jelmer P. Gaast & Ivo J. B. F. Adan & René B. M. Koster, 2017. "The analysis of batch sojourn-times in polling systems," Queueing Systems: Theory and Applications, Springer, vol. 85(3), pages 313-335, April.
    18. So, Kut C. & Zheng, Xiaona, 2003. "Impact of supplier's lead time and forecast demand updating on retailer's order quantity variability in a two-level supply chain," International Journal of Production Economics, Elsevier, vol. 86(2), pages 169-179, November.
    19. Christos Langaris, 1999. "Markovian polling systems with mixed service disciplines and retrial customers," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 7(2), pages 305-322, December.
    20. Subba Rao, S. & Gunasekaran, A. & Goyal, S. K. & Martikainen, T., 1998. "Waiting line model applications in manufacturing," International Journal of Production Economics, Elsevier, vol. 54(1), pages 1-28, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:53:y:2007:i:6:p:991-1004. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.