IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v50y2004i5p658-669.html
   My bibliography  Save this article

Flow Shop Scheduling with Partial Resource Flexibility

Author

Listed:
  • Richard L. Daniels

    (Terry College of Business, University of Georgia, Athens, Georgia 30602.)

  • Joseph B. Mazzola

    (McDonough School of Business, Georgetown University, Washington, D.C. 20057.)

  • Dailun Shi

    (IBM T. J. Watson Research Center, 19 Skyline Drive, Hawthorne, New York 10532.)

Abstract

Resource flexibility refers to the ability to dynamically reallocate units of resource from one stage of a production process to another in response to shifting bottlenecks. Recent research has demonstrated that substantial improvements in operational performance can be realized in both serial- and parallel-machine production environments through the effective utilization of resource flexibility. In these contexts the resource was assumed to exhibit complete flexibility. This research explores the extent to which the operational benefits associated with resource flexibility can be achieved in a flow shop environment using a partially flexible resource. Focusing on labor flexibility, we propose corresponding metrics for partial flexibility and formulate a model for flow shop scheduling with partial resource flexibility. On the basis of computational experiments, we explore properties pertaining to the relative amounts as well as the allocation of partial resource flexibility as it is distributed across the workforce. The conclusions drawn from this research provide significant insight into the management of flow shops with a workforce that is crosstrained to achieve partial flexibility. Moreover, we extend the principles developed by Jordan and Graves (1995) for partially flexible manufacturing plants to the flow shop scheduling environment, and we link these principles in a novel way to recent research on self-buffering flow lines.

Suggested Citation

  • Richard L. Daniels & Joseph B. Mazzola & Dailun Shi, 2004. "Flow Shop Scheduling with Partial Resource Flexibility," Management Science, INFORMS, vol. 50(5), pages 658-669, May.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:5:p:658-669
    DOI: 10.1287/mnsc.1040.0209
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1040.0209
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.1040.0209?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. Emil Zavadlav & John O. McClain & L. Joseph Thomas, 1996. "Self-Buffering, Self-Balancing, Self-Flushing Production Lines," Management Science, INFORMS, vol. 42(8), pages 1151-1164, August.
    2. Richard L. Daniels & Joseph B. Mazzola, 1994. "Flow Shop Scheduling with Resource Flexibility," Operations Research, INFORMS, vol. 42(3), pages 504-522, June.
    3. Van Wassenhove, Luk N. & Baker, Kenneth R., 1982. "A bicriterion approach to time/cost trade-offs in sequencing," European Journal of Operational Research, Elsevier, vol. 11(1), pages 48-54, September.
    4. F. Brian Talbot, 1982. "Resource-Constrained Project Scheduling with Time-Resource Tradeoffs: The Nonpreemptive Case," Management Science, INFORMS, vol. 28(10), pages 1197-1210, October.
    5. William C. Jordan & Stephen C. Graves, 1995. "Principles on the Benefits of Manufacturing Process Flexibility," Management Science, INFORMS, vol. 41(4), pages 577-594, April.
    6. Michael A. Trick, 1994. "Scheduling Multiple Variable-Speed Machines," Operations Research, INFORMS, vol. 42(2), pages 234-248, April.
    7. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    8. John J. Bartholdi & Donald D. Eisenstein, 1996. "A Production Line that Balances Itself," Operations Research, INFORMS, vol. 44(1), pages 21-34, February.
    9. Lawrence, Stephen R. & Morton, Thomas E., 1993. "Resource-constrained multi-project scheduling with tardy costs: Comparing myopic, bottleneck, and resource pricing heuristics," European Journal of Operational Research, Elsevier, vol. 64(2), pages 168-187, January.
    10. Richard L. Daniels & Barbara J. Hoopes & Joseph B. Mazzola, 1996. "Scheduling Parallel Manufacturing Cells with Resource Flexibility," Management Science, INFORMS, vol. 42(9), pages 1260-1276, September.
    11. Richard Daniels & Barbara Hoopes & Joseph Mazzola, 1997. "An analysis of heuristics for the parallel-machine flexible-resource scheduling problem," Annals of Operations Research, Springer, vol. 70(0), pages 439-472, April.
    12. Charles H. Fine & Robert M. Freund, 1990. "Optimal Investment in Product-Flexible Manufacturing Capacity," Management Science, INFORMS, vol. 36(4), pages 449-466, April.
    13. Chung-Yee Lee & Lei Lei & Michael Pinedo, 1997. "Current trends in deterministic scheduling," Annals of Operations Research, Springer, vol. 70(0), pages 1-41, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhenzhen Yan & Sarah Yini Gao & Chung Piaw Teo, 2018. "On the Design of Sparse but Efficient Structures in Operations," Management Science, INFORMS, vol. 64(7), pages 3421-3445, July.
    2. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    3. Nigel Wadeson, 2013. "The Division of Labour under Uncertainty," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 169(2), pages 253-274, June.
    4. Atif Açıkgöz & Ayşe Günsel & Cemil Kuzey & Halil Zaim, 2016. "Team Foresight in New Product Development Projects," Group Decision and Negotiation, Springer, vol. 25(2), pages 289-323, March.
    5. Ma, Ran & Guo, Sainan & Miao, Cuixia, 2021. "A semi-online algorithm and its competitive analysis for parallel-machine scheduling problem with rejection," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    6. Olivella, Jordi & Nembhard, David, 2016. "Calibrating cross-training to meet demand mix variation and employee absence," European Journal of Operational Research, Elsevier, vol. 248(2), pages 462-472.
    7. Miloš Milenković & Susana Val & Nebojša Bojović, 2023. "Simultaneous lot sizing and scheduling in the animal feed premix industry," Operational Research, Springer, vol. 23(2), pages 1-40, June.
    8. Gultekin, Hakan, 2012. "Scheduling in flowshops with flexible operations: Throughput optimization and benefits of flexibility," International Journal of Production Economics, Elsevier, vol. 140(2), pages 900-911.
    9. Pei, Jun & Liu, Xinbao & Fan, Wenjuan & Pardalos, Panos M. & Lu, Shaojun, 2019. "A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers," Omega, Elsevier, vol. 82(C), pages 55-69.

    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. Wallace J. Hopp & Eylem Tekin & Mark P. Van Oyen, 2004. "Benefits of Skill Chaining in Serial Production Lines with Cross-Trained Workers," Management Science, INFORMS, vol. 50(1), pages 83-98, January.
    2. Sigrún Andradóttir & Hayriye Ayhan & Douglas G. Down, 2007. "Compensating for Failures with Flexible Servers," Operations Research, INFORMS, vol. 55(4), pages 753-768, August.
    3. Achal Bassamboo & Ramandeep S. Randhawa & Jan A. Van Mieghem, 2012. "A Little Flexibility Is All You Need: On the Asymptotic Value of Flexible Capacity in Parallel Queuing Systems," Operations Research, INFORMS, vol. 60(6), pages 1423-1435, December.
    4. Sigrún Andradóttir & Hayriye Ayhan & Douglas G. Down, 2001. "Server Assignment Policies for Maximizing the Steady-State Throughput of Finite Queueing Systems," Management Science, INFORMS, vol. 47(10), pages 1421-1439, October.
    5. Brian Tomlin & Yimin Wang, 2005. "On the Value of Mix Flexibility and Dual Sourcing in Unreliable Newsvendor Networks," Manufacturing & Service Operations Management, INFORMS, vol. 7(1), pages 37-57, June.
    6. Vo[ss], Stefan & Witt, Andreas, 2007. "Hybrid flow shop scheduling as a multi-mode multi-project scheduling problem with batching requirements: A real-world application," International Journal of Production Economics, Elsevier, vol. 105(2), pages 445-458, February.
    7. T.C.E. Cheng & B.M.T. Lin & A. Toker, 2000. "Makespan minimization in the two‐machine flowshop batch scheduling problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(2), pages 128-144, March.
    8. Francas, David & Löhndorf, Nils & Minner, Stefan, 2011. "Machine and labor flexibility in manufacturing networks," International Journal of Production Economics, Elsevier, vol. 131(1), pages 165-174, May.
    9. Manu Goyal & Serguei Netessine, 2007. "Strategic Technology Choice and Capacity Investment Under Demand Uncertainty," Management Science, INFORMS, vol. 53(2), pages 192-207, February.
    10. Dvir Shabtay & Moshe Kaspi, 2006. "Minimizing the makespan in open‐shop scheduling problems with a convex resource consumption function," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(3), pages 204-216, April.
    11. Gregory Dobson & Tolga Tezcan & Vera Tilson, 2013. "Optimal Workflow Decisions for Investigators in Systems with Interruptions," Management Science, INFORMS, vol. 59(5), pages 1125-1141, May.
    12. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    13. Bo Liao & Candace Arai Yano & Shiva Esturi, 2017. "Optimizing Site Qualification Across the Supply Network at Western Digital," Interfaces, INFORMS, vol. 47(4), pages 305-319, August.
    14. Seyed M. Iravani & Mark P. Van Oyen & Katharine T. Sims, 2005. "Structural Flexibility: A New Perspective on the Design of Manufacturing and Service Operations," Management Science, INFORMS, vol. 51(2), pages 151-166, February.
    15. Anantaram Balakrishnan & Joseph Geunes, 2000. "Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning," Manufacturing & Service Operations Management, INFORMS, vol. 2(2), pages 166-185, January.
    16. Elena Katok & William Tarantino & Terry P. Harrison, 2003. "Investment in production resource flexibility: An empirical investigation of methods for planning under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(2), pages 105-129, March.
    17. Onur Boyabatlı & Tiecheng Leng & L. Beril Toktay, 2016. "The Impact of Budget Constraints on Flexible vs. Dedicated Technology Choice," Management Science, INFORMS, vol. 62(1), pages 225-244, January.
    18. Jörn Grahl & Michael Schneider & David Francas, 2010. "A Problem-Specific and Effective Metaheuristic for Flexibility Design," Working Papers 1001, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 28 Jan 2010.
    19. Dayal Madhukar & Verma, Sanjay, 2015. "Multi-processor Exact Procedures for Regular Measures of the Multi-mode RCPSP," IIMA Working Papers WP2015-03-25, Indian Institute of Management Ahmedabad, Research and Publication Department.
    20. Robert A. Shumsky & Fuqiang Zhang, 2009. "Dynamic Capacity Management with Substitution," Operations Research, INFORMS, vol. 57(3), pages 671-684, June.

    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:50:y:2004:i:5:p:658-669. 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.