IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v43y2013i6p518-529.html
   My bibliography  Save this article

Optimization Models for Production Planning in LG Display

Author

Listed:
  • Seokcheol Chang

    (SCM Team, LG Display Co., Ltd., 150-721 Seoul, South Korea)

  • Jaewoo Chung

    (School of Business Administration, Kyungpook National University–Daegu, 702-701 South Korea)

Abstract

This paper introduces an application for production planning based on multiple linear programming models for a light-emitting diode (LED) array assembly. The proposed method, multirank mixing (MRM) optimization, focuses on reducing the inventory level of the LED parts used for various electronic devices, while also meeting customer demands. In this industry, high inventory levels result in high scrap rates for LED parts because product models change frequently. Therefore, maintaining low inventory levels is critical. MRM optimization determines the best combination of LED parts for each assembly step, given inventory levels of LED parts with varying quality characteristics. The results of our performance testing show that our proposed method outperforms a heuristic method that requires intensive effort by human planners. When LG Display used MRM optimization at one of its LED manufacturing facilities, the scrap rate for LED packages decreased substantially.

Suggested Citation

  • Seokcheol Chang & Jaewoo Chung, 2013. "Optimization Models for Production Planning in LG Display," Interfaces, INFORMS, vol. 43(6), pages 518-529, December.
  • Handle: RePEc:inm:orinte:v:43:y:2013:i:6:p:518-529
    DOI: 10.1287/inte.2013.0698
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2013.0698
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2013.0698?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. Chen, Kejia & Ji, Ping, 2007. "A mixed integer programming model for advanced planning and scheduling (APS)," European Journal of Operational Research, Elsevier, vol. 181(1), pages 515-522, August.
    2. Gerald Brown & Joseph Keegan & Brian Vigus & Kevin Wood, 2001. "The Kellogg Company Optimizes Production, Inventory, and Distribution," Interfaces, INFORMS, vol. 31(6), pages 1-15, December.
    3. Jennifer L. Loveland & Susan K. Monkman & Douglas J. Morrice, 2007. "Dell Uses a New Production-Scheduling Algorithm to Accommodate Increased Product Variety," Interfaces, INFORMS, vol. 37(3), pages 209-219, June.
    4. Victor Portougal & David J. Robb, 2000. "Production Scheduling Theory: Just Where Is It Applicable?," Interfaces, INFORMS, vol. 30(6), pages 64-76, December.
    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. Z. Caner Taşkın & Semra Ağralı & A. Tamer Ünal & Vahdet Belada & Filiz Gökten-Yılmaz, 2015. "Mathematical Programming-Based Sales and Operations Planning at Vestel Electronics," Interfaces, INFORMS, vol. 45(4), pages 325-340, August.
    2. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.

    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. Singer, Marcos & Donoso, Patricio, 2008. "Empirical validation of an activity-based optimization system," International Journal of Production Economics, Elsevier, vol. 113(1), pages 335-345, May.
    2. Khalil Tliba & Thierno M. L. Diallo & Olivia Penas & Romdhane Ben Khalifa & Noureddine Ben Yahia & Jean-Yves Choley, 2023. "Digital twin-driven dynamic scheduling of a hybrid flow shop," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2281-2306, June.
    3. Habibi, M.K. Khakim & Battaïa, Olga & Cung, Van-Dat & Dolgui, Alexandre, 2017. "Collection-disassembly problem in reverse supply chain," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 334-344.
    4. Kristianto, Yohanes & Helo, Petri, 2015. "Reprint of “Product architecture modularity implications for operations economy of green supply chains”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 74(C), pages 63-80.
    5. Stüve, David & van der Meer, Robert & Lütke Entrup, Matthias & Agha, Mouhamad Shaker Ali, 2020. "Supply chain planning in the food industry," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 317-353, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Hrabec, Dušan & Hvattum, Lars Magnus & Hoff, Arild, 2022. "The value of integrated planning for production, inventory, and routing decisions: A systematic review and meta-analysis," International Journal of Production Economics, Elsevier, vol. 248(C).
    7. Atan, Zümbül & Ahmadi, Taher & Stegehuis, Clara & Kok, Ton de & Adan, Ivo, 2017. "Assemble-to-order systems: A review," European Journal of Operational Research, Elsevier, vol. 261(3), pages 866-879.
    8. George Dikos & Stavroula Spyropoulou, 2013. "Supply Chain Optimization and Planning in Heracles General Cement Company," Interfaces, INFORMS, vol. 43(4), pages 297-312, August.
    9. Erick Miranda-Meza & Iván Derpich & Juan M. Sepúlveda, 2024. "An Icon-Based Methodology for the Design of a Prototype of a Multi-Process, Multi-Product, Aggregated Production Planning Software," Mathematics, MDPI, vol. 12(2), pages 1-25, January.
    10. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.
    11. Chen, Liang-Tu, 2014. "Optimal dynamic policies for integrated production and marketing planning in business-to-business marketplaces," International Journal of Production Economics, Elsevier, vol. 153(C), pages 46-53.
    12. Lin, Chinho & Chow, Wing S. & Madu, Christian N. & Kuei, Chu-Hua & Pei Yu, Pei, 2005. "A structural equation model of supply chain quality management and organizational performance," International Journal of Production Economics, Elsevier, vol. 96(3), pages 355-365, June.
    13. Javier Faulin & Pablo Sarobe & Jorge Simal, 2005. "The DSS LOGDIS Optimizes Delivery Routes for FRILAC’s Frozen Products," Interfaces, INFORMS, vol. 35(3), pages 202-214, June.
    14. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2014. "Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem," Transportation Science, INFORMS, vol. 48(1), pages 20-45, February.
    15. Boudia, M. & Prins, C., 2009. "A memetic algorithm with dynamic population management for an integrated production-distribution problem," European Journal of Operational Research, Elsevier, vol. 195(3), pages 703-715, June.
    16. Jack G.A.J. van der Vorst & Joost Snels, 2014. "Developments and Needs for Sustainable Agro-Logistics in Developing Countries," World Bank Publications - Reports 17834, The World Bank Group.
    17. Ilkyeong Moon & Yoon Jea Jeong & Subrata Saha, 2016. "Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint," Sustainability, MDPI, vol. 8(8), pages 1-17, August.
    18. Kusumastuti, Ratih Dyah & Donk, Dirk Pieter van & Teunter, Ruud, 2016. "Crop-related harvesting and processing planning: a review," International Journal of Production Economics, Elsevier, vol. 174(C), pages 76-92.
    19. Soysal, Mehmet & Bloemhof-Ruwaard, Jacqueline.M. & Meuwissen, Miranda P.M. & van der Vorst, Jack G.A.J., 2012. "A Review on Quantitative Models for Sustainable Food Logistics Management," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 3(2), pages 1-20, December.
    20. Zakaria Chekoubi & Wajdi Trabelsi & Nathalie Sauer & Ilias Majdouline, 2022. "The Integrated Production-Inventory-Routing Problem with Reverse Logistics and Remanufacturing: A Two-Phase Decomposition Heuristic," Sustainability, MDPI, vol. 14(20), pages 1-30, October.

    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:orinte:v:43:y:2013:i:6:p:518-529. 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.