IDEAS home Printed from https://ideas.repec.org/a/ids/ijiscm/v7y2014i1p70-91.html
   My bibliography  Save this article

Development of an integrated demand-supply balancing system for supply chain exception handling

Author

Listed:
  • Li-Chih Wang
  • Chen-Yang Cheng

Abstract

Most enterprises are suffering information invisibility in multi-site production supply chain information. Without appropriate information transparency, supply chain exception such as due date changes, and material shortage usually increase the planning complexity. In addition, the balance of supply and demand for each distinct manufacturing site simultaneously is quite difficult to maintain. Therefore, this study develops an integrated demand-supply balancing (IDSB) system framework and takes a textile company that has implemented the IDSB system to demonstrate how the IDSB system to handle supply chain exception. DSB function justifies the feasibility of each reallocation plan in terms of supply and demand balancing perspective. Finally, a textile company case study shows that the IDSB system can indeed support global production planners to effectively generate more feasible multi-site master production schedule and reallocation plan than traditional approach in terms of available material, capacity and order due date.

Suggested Citation

  • Li-Chih Wang & Chen-Yang Cheng, 2014. "Development of an integrated demand-supply balancing system for supply chain exception handling," International Journal of Information Systems and Change Management, Inderscience Enterprises Ltd, vol. 7(1), pages 70-91.
  • Handle: RePEc:ids:ijiscm:v:7:y:2014:i:1:p:70-91
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=65059
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    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. Pham, An & Jin, Tongdan & Novoa, Clara & Qin, Jin, 2019. "A multi-site production and microgrid planning model for net-zero energy operations," International Journal of Production Economics, Elsevier, vol. 218(C), pages 260-274.
    2. Chia-Nan Wang & Nhat-Luong Nhieu & Trang Thi Thu Tran, 2021. "Stochastic Chebyshev Goal Programming Mixed Integer Linear Model for Sustainable Global Production Planning," Mathematics, MDPI, vol. 9(5), pages 1-22, February.
    3. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    4. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.
    5. Sivadasan, Suja & Smart, Janet & Huaccho Huatuco, Luisa & Calinescu, Anisoara, 2013. "Reducing schedule instability by identifying and omitting complexity-adding information flows at the supplier–customer interface," International Journal of Production Economics, Elsevier, vol. 145(1), pages 253-262.
    6. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    7. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).
    8. Hasuike, Takashi & Ishii, Hiroaki, 2009. "On flexible product-mix decision problems under randomness and fuzziness," Omega, Elsevier, vol. 37(4), pages 770-787, August.
    9. Louly, Mohamed-Aly & Dolgui, Alexandre, 2011. "Optimal time phasing and periodicity for MRP with POQ policy," International Journal of Production Economics, Elsevier, vol. 131(1), pages 76-86, May.
    10. Xinbo Zhang & Feng Zhang & Xiaohong Chen & Zhong Wan, 2014. "Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems," Journal of Optimization, Hindawi, vol. 2014, pages 1-10, February.
    11. Sodhi, ManMohan S. & Tang, Christopher S., 2009. "Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset-liability management," International Journal of Production Economics, Elsevier, vol. 121(2), pages 728-738, October.
    12. Nadeau, Marie-Claude & Kar, Ashish & Roth, Richard & Kirchain, Randolph, 2010. "A dynamic process-based cost modeling approach to understand learning effects in manufacturing," International Journal of Production Economics, Elsevier, vol. 128(1), pages 223-234, November.
    13. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    14. Kumar, Kunal & Aouam, Tarik, 2019. "Extending the strategic safety stock placement model to consider tactical production smoothing," European Journal of Operational Research, Elsevier, vol. 279(2), pages 429-448.
    15. Tang, Christopher S., 2010. "A review of marketing-operations interface models: From co-existence to coordination and collaboration," International Journal of Production Economics, Elsevier, vol. 125(1), pages 22-40, May.
    16. Michiel A. J. uit het Broek & Ruud H. Teunter & Bram de Jonge & Jasper Veldman & Nicky D. Van Foreest, 2020. "Condition-Based Production Planning: Adjusting Production Rates to Balance Output and Failure Risk," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 792-811, July.
    17. A. Negahban & J.S. Smith, 2016. "The effect of supply and demand uncertainties on the optimal production and sales plans for new products," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3852-3869, July.
    18. Amy David & David Farr & Ross Januszyk & Urmila Diwekar, 2015. "USG Uses Stochastic Optimization to Lower Distribution Costs," Interfaces, INFORMS, vol. 45(3), pages 216-227, June.
    19. Omoruyi Osayuwamen & Mafini Chengedzai, 2016. "Supply Chain Management and Customer Satisfaction in Small to Medium Enterprises," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 61(3), pages 43-58, December.
    20. Huthaifa AL-Khazraji & Colin Cole & William Guo, 2021. "Optimization and Simulation of Dynamic Performance of Production–Inventory Systems with Multivariable Controls," Mathematics, MDPI, vol. 9(5), pages 1-13, March.

    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:ids:ijiscm:v:7:y:2014:i:1:p:70-91. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=79 .

    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.