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The impact of design uncertainty in engineer-to-order project planning

Author

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  • Vaagen, Hajnalka
  • Kaut, Michal
  • Wallace, Stein W.

Abstract

A major driver of planning complexity in engineer-to-order (ETO) projects is design uncertainty far into the engineering and production processes. This leads to uncertainty in technical information and will typically lead to a revision of parts of the project network itself. Hence, this uncertainty is different from standard task completion uncertainty. We build a stochastic program to draw attention to, and analyse, the engineering-design planning problem, and in particular, to understand what role design flexibility plays in hedging against such uncertainty. The purpose is not to devise a general stochastic dynamic model to be used in practice, but to demonstrate by the use of small model instances how design flexibility actually adds value to a project and what, exactly, it is that produces this value. This will help us understand better where and when to develop flexibility and buffers, even when not actually solving stochastic models.

Suggested Citation

  • Vaagen, Hajnalka & Kaut, Michal & Wallace, Stein W., 2017. "The impact of design uncertainty in engineer-to-order project planning," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1098-1109.
  • Handle: RePEc:eee:ejores:v:261:y:2017:i:3:p:1098-1109
    DOI: 10.1016/j.ejor.2017.03.005
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    References listed on IDEAS

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    1. Vaagen, Hajnalka & Wallace, Stein W. & Kaut, Michal, 2011. "Modelling consumer-directed substitution," International Journal of Production Economics, Elsevier, vol. 134(2), pages 388-397, December.
    2. Herroelen, Willy & Demeulemeester, Erik & De Reyck, Bert, 2001. "A note on the paper "Resource-constrained project scheduling: Notation, classification, models and methods" by Brucker et al," European Journal of Operational Research, Elsevier, vol. 128(3), pages 679-688, February.
    3. Stijn Vonder & Erik Demeulemeester & Roel Leus & Willy Herroelen, 2006. "Proactive-Reactive Project Scheduling Trade-Offs and Procedures," International Series in Operations Research & Management Science, in: Joanna Józefowska & Jan Weglarz (ed.), Perspectives in Modern Project Scheduling, chapter 0, pages 25-51, Springer.
    4. Francesca Maggioni & Stein Wallace, 2012. "Analyzing the quality of the expected value solution in stochastic programming," Annals of Operations Research, Springer, vol. 200(1), pages 37-54, November.
    5. Jorgensen, Trond & Wallace, Stein W., 2000. "Improving project cost estimation by taking into account managerial flexibility," European Journal of Operational Research, Elsevier, vol. 127(2), pages 239-251, December.
    6. Artigues, Christian & Billaut, Jean-Charles & Esswein, Carl, 2005. "Maximization of solution flexibility for robust shop scheduling," European Journal of Operational Research, Elsevier, vol. 165(2), pages 314-328, September.
    7. Biju Thapalia & Stein Wallace & Michal Kaut & Teodor Crainic, 2012. "Single source single-commodity stochastic network design," Computational Management Science, Springer, vol. 9(1), pages 139-160, February.
    8. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    9. Deblaere, Filip & Demeulemeester, Erik & Herroelen, Willy, 2011. "Proactive policies for the stochastic resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 214(2), pages 308-316, October.
    10. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    11. Stein Wallace, 2010. "Stochastic programming and the option of doing it differently," Annals of Operations Research, Springer, vol. 177(1), pages 3-8, June.
    12. Thapalia, Biju K. & Crainic, Teodor Gabriel & Kaut, Michal & Wallace, Stein W., 2012. "Single-commodity network design with random edge capacities," European Journal of Operational Research, Elsevier, vol. 220(2), pages 394-403.
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    Cited by:

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    5. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    6. Dmitriy Demin & Horst Schwickerath & Katharina Schwickerath, 2020. "Network Planning Of The Publishing Process For The Issue Of The Magazine," Post-Print hal-03021325, HAL.
    7. Fernanda Saidelles Bataglin & Daniela Dietz Viana & Carlos Torres Formoso, 2022. "Design Principles and Prescriptions for Planning and Controlling Engineer-to-Order Industrialized Building Systems," Sustainability, MDPI, vol. 14(24), pages 1-22, December.
    8. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    9. Alfnes, Erlend & Gosling, Jonathan & Naim, Mohamed & Dreyer, Heidi C., 2021. "Exploring systemic factors creating uncertainty in complex engineer-to-order supply chains: Case studies from Norwegian shipbuilding first tier suppliers," International Journal of Production Economics, Elsevier, vol. 240(C).
    10. Mile Katic & Renu Agarwal, 2018. "The Flexibility Paradox: Achieving Ambidexterity in High-Variety, Low-Volume Manufacturing," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(1), pages 69-86, March.
    11. Demin Dmitriy & Schwickerath Horst & Schwickerath Katharina, 2020. "Network planning of the publishing process for the issue of the magazine," Technology audit and production reserves, Socionet;Technology audit and production reserves, vol. 5(4(55)), pages 23-28.
    12. Alfnes, Erlend & Gosling, Jonathan & Naim, Mohamed & Dreyer, Heidi C., 2023. "Rearticulating supply chain design and operation principles to mitigate uncertainty in the Norwegian engineer-to-order shipbuilding sector," International Journal of Production Economics, Elsevier, vol. 262(C).

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