IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v134y2011i2p322-332.html
   My bibliography  Save this article

Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations

Author

Listed:
  • Rastogi, Aditya P.
  • Fowler, John W.
  • Matthew Carlyle, W.
  • Araz, Ozgur M.
  • Maltz, Arnold
  • Büke, Burak

Abstract

A semiconductor supply network involves many expensive steps, which have to be executed to serve global markets. The complexity of global capacity planning combined with the large capital expenditures to increase factory capacity makes it important to incorporate optimization methodologies for cost reduction and long-term planning. The typical view of a semiconductor supply network consists of layers for wafer fab, sort, assembly, test and demand centers. We present a two-stage stochastic integer-programming formulation to model a semiconductor supply network. The model makes strategic capacity decisions, (i.e., build factories or outsource) while accounting for the uncertainties in demand for multiple products. We use the model not only to analyze how variability in demand affects the make/buy decisions but also to investigate how the correlation between demands of different products affects these strategic decisions. Finally, we demonstrate the value of incorporating demand uncertainty into a decision-making scheme.

Suggested Citation

  • Rastogi, Aditya P. & Fowler, John W. & Matthew Carlyle, W. & Araz, Ozgur M. & Maltz, Arnold & Büke, Burak, 2011. "Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations," International Journal of Production Economics, Elsevier, vol. 134(2), pages 322-332, December.
    • Handle: RePEc:eee:proeco:v:134:y:2011:i:2:p:322-332
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527309004083
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Swaminathan, Jayashankar M., 2000. "Tool capacity planning for semiconductor fabrication facilities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 120(3), pages 545-558, February.
    2. Azaron, A. & Brown, K.N. & Tarim, S.A. & Modarres, M., 2008. "A multi-objective stochastic programming approach for supply chain design considering risk," International Journal of Production Economics, Elsevier, vol. 116(1), pages 129-138, November.
    3. Goh, Mark & Lim, Joseph Y.S. & Meng, Fanwen, 2007. "A stochastic model for risk management in global supply chain networks," European Journal of Operational Research, Elsevier, vol. 182(1), pages 164-173, October.
    4. Thanh, Phuong Nga & Bostel, Nathalie & Péton, Olivier, 2008. "A dynamic model for facility location in the design of complex supply chains," International Journal of Production Economics, Elsevier, vol. 113(2), pages 678-693, June.
    5. Leung, Stephen C.H. & Tsang, Sally O.S. & Ng, W.L. & Wu, Yue, 2007. "A robust optimization model for multi-site production planning problem in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 181(1), pages 224-238, August.
    6. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    7. Stein W. Wallace, 2000. "Decision Making Under Uncertainty: Is Sensitivity Analysis of Any Use?," Operations Research, INFORMS, vol. 48(1), pages 20-25, February.
    8. C Lucas & S A MirHassani & G Mitra & C A Poojari, 2001. "An application of Lagrangian relaxation to a capacity planning problem under uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(11), pages 1256-1266, November.
    9. Stein W. Wallace & Stein-Erik Fleten, 2002. "Stochastic programming in energy," GE, Growth, Math methods 0201001, University Library of Munich, Germany, revised 13 Nov 2003.
    10. Chouinard, Marc & D'Amours, Sophie & Aït-Kadi, Daoud, 2008. "A stochastic programming approach for designing supply loops," International Journal of Production Economics, Elsevier, vol. 113(2), pages 657-677, June.
    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. Martínez-Costa, Carme & Mas-Machuca, Marta & Benedito, Ernest & Corominas, Albert, 2014. "A review of mathematical programming models for strategic capacity planning in manufacturing," International Journal of Production Economics, Elsevier, vol. 153(C), pages 66-85.
    2. Qiao Guangshun & Lu Yulin, 2024. "Operating Efficiency in the Capital-Intensive Semiconductor Industry: A Nonparametric Frontier Approach," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 18(1), pages 1-17, January.
    3. Birisci, Esma & McGarvey, Ronald G., 2022. "Cost-versus environmentally-optimal production in institutional food service operations," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    4. Hahn, G.J. & Kuhn, H., 2012. "Simultaneous investment, operations, and financial planning in supply chains: A value-based optimization approach," International Journal of Production Economics, Elsevier, vol. 140(2), pages 559-569.
    5. Thorbecke, Willem, 2019. "Why Japan lost its comparative advantage in producing electronic parts and components," Journal of the Japanese and International Economies, Elsevier, vol. 54(C).
    6. Lin, James T. & Chen, Tzu-Li & Chu, Hsiao-Ching, 2014. "A stochastic dynamic programming approach for multi-site capacity planning in TFT-LCD manufacturing under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 148(C), pages 21-36.
    7. Yu, Yu & Ma, Daipeng & Wang, Yong, 2024. "Structural resilience evolution and vulnerability assessment of semiconductor materials supply network in the global semiconductor industry," International Journal of Production Economics, Elsevier, vol. 270(C).

    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. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    2. Mohammaddust, Faeghe & Rezapour, Shabnam & Farahani, Reza Zanjirani & Mofidfar, Mohammad & Hill, Alex, 2017. "Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 632-653.
    3. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    4. Sahling, Florian & Kayser, Ariane, 2016. "Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty," Omega, Elsevier, vol. 59(PB), pages 201-214.
    5. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    6. Vahid Nooraie, S. & Parast, Mahour Mellat, 2016. "Mitigating supply chain disruptions through the assessment of trade-offs among risks, costs and investments in capabilities," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 8-21.
    7. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    8. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    9. Govindan, Kannan & Fattahi, Mohammad, 2017. "Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 680-699.
    10. Alonso-Ayuso, Antonio & Carvallo, Felipe & Escudero, Laureano F. & Guignard, Monique & Pi, Jiaxing & Puranmalka, Raghav & Weintraub, Andrés, 2014. "Medium range optimization of copper extraction planning under uncertainty in future copper prices," European Journal of Operational Research, Elsevier, vol. 233(3), pages 711-726.
    11. Seyyed Mohammad Seyyed Alizadeh Ganji & Mohammad Hayati, 2016. "Identifying and Assessing the Risks in the Supply Chain," Modern Applied Science, Canadian Center of Science and Education, vol. 10(6), pages 1-74, June.
    12. Rezapour, Shabnam & Allen, Janet K. & Mistree, Farrokh, 2015. "Uncertainty propagation in a supply chain or supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 185-206.
    13. Roba W. Salem & Mohamed Haouari, 2017. "A simulation-optimisation approach for supply chain network design under supply and demand uncertainties," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1845-1861, April.
    14. Mengfei Chen & Mohamed Kharbeche & Mohamed Haouari & Weihong Grace Guo, 2024. "A simulation-optimization framework for food supply chain network design to ensure food accessibility under uncertainty," Papers 2406.04439, arXiv.org, revised Jun 2024.
    15. Azaron, A. & Brown, K.N. & Tarim, S.A. & Modarres, M., 2008. "A multi-objective stochastic programming approach for supply chain design considering risk," International Journal of Production Economics, Elsevier, vol. 116(1), pages 129-138, November.
    16. Blossey, Gregor & Hahn, Gerd J. & Koberstein, Achim, 2022. "Planning pharmaceutical manufacturing networks in the light of uncertain production approval times," International Journal of Production Economics, Elsevier, vol. 244(C).
    17. Mingqiang Yin & Min Huang & Xiaohu Qian & Dazhi Wang & Xingwei Wang & Loo Hay Lee, 2023. "Fourth-party logistics network design with service time constraint under stochastic demand," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1203-1227, March.
    18. Aydin, Nezir & Murat, Alper, 2013. "A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem," International Journal of Production Economics, Elsevier, vol. 145(1), pages 173-183.
    19. Fatemeh Sarayloo & Teodor Gabriel Crainic & Walter Rei, 2021. "A Learning-Based Matheuristic for Stochastic Multicommodity Network Design," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 643-656, May.
    20. Gholami-Zanjani, Seyed Mohammad & Klibi, Walid & Jabalameli, Mohammad Saeed & Pishvaee, Mir Saman, 2021. "The design of resilient food supply chain networks prone to epidemic disruptions," International Journal of Production Economics, Elsevier, vol. 233(C).

    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:eee:proeco:v:134:y:2011:i:2:p:322-332. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.