IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v69y2017icp29-42.html
   My bibliography  Save this article

Learning and Bayesian updating in long cycle made-to-order (MTO) production

Author

Listed:
  • Womer, K.
  • Li, H.
  • Camm, J.
  • Osterman, C.
  • Radhakrishnan, R.

Abstract

We model production planning for made-to-order (MTO) manufacturing by choosing production rate to minimize expected discounted cost incurred up to a promised delivery date. Products that are MTO are often unique and customized. The associated learning curve slope and other production parameters cannot be precisely estimated before production starts. In this paper, a dynamic and adaptive approach to estimate the effects of learning and to optimize next period production is developed. This approach offers a closed-loop solution through stochastic dynamic programming. Monthly production data are used to update the joint probability distributions of production parameters via Bayesian methods. Our approach is illustrated using historical earned-value data from the Black Hawk Helicopter Program. Managerial insights are obtained and discussed.

Suggested Citation

  • Womer, K. & Li, H. & Camm, J. & Osterman, C. & Radhakrishnan, R., 2017. "Learning and Bayesian updating in long cycle made-to-order (MTO) production," Omega, Elsevier, vol. 69(C), pages 29-42.
    • Handle: RePEc:eee:jomega:v:69:y:2017:i:c:p:29-42
    DOI: 10.1016/j.omega.2016.07.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048316304522
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2016.07.007?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
    ---><---

    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. Saman Majd & Robert S. Pindyck, 1989. "The Learning Curve and Optimal Production under Uncertainty," RAND Journal of Economics, The RAND Corporation, vol. 20(3), pages 331-343, Autumn.
    2. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-1064, September.
    3. Joseph B. Mazzola & Kevin F. McCardle, 1996. "A Bayesian Approach to Managing Learning-Curve Uncertainty," Management Science, INFORMS, vol. 42(5), pages 680-692, May.
    4. Joseph B. Mazzola & Kevin F. McCardle, 1997. "The Stochastic Learning Curve: Optimal Production in the Presence of Learning-Curve Uncertainty," Operations Research, INFORMS, vol. 45(3), pages 440-450, June.
    5. Allen C. Miller, III & Thomas R. Rice, 1983. "Discrete Approximations of Probability Distributions," Management Science, INFORMS, vol. 29(3), pages 352-362, March.
    6. Tarakci, Hakan & Tang, Kwei & Teyarachakul, Sunantha, 2009. "Learning effects on maintenance outsourcing," European Journal of Operational Research, Elsevier, vol. 192(1), pages 138-150, January.
    7. Steven A. Lippman & Kevin F. McCardle, 1991. "Uncertain Search: A Model of Search Among Technologies of Uncertain Values," Management Science, INFORMS, vol. 37(11), pages 1474-1490, November.
    8. Sáenz-Royo, Carlos & Salas-Fumás, Vicente, 2013. "Learning to learn and productivity growth: Evidence from a new car-assembly plant," Omega, Elsevier, vol. 41(2), pages 336-344.
    9. Norman Keith Womer, 1979. "Learning Curves, Production Rate, and Program Costs," Management Science, INFORMS, vol. 25(4), pages 312-319, April.
    10. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    11. Vits, Jeroen & Gelders, Ludo & Pintelon, Liliane, 2006. "Production process changes: A dynamic programming approach to manage effective capacity and experience," International Journal of Production Economics, Elsevier, vol. 104(2), pages 473-481, December.
    12. Ronald J. Ebert, 1976. "Aggregate Planning with Learning Curve Productivity," Management Science, INFORMS, vol. 23(2), pages 171-182, October.
    13. 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.
    14. Vanhoucke, Mario, 2011. "On the dynamic use of project performance and schedule risk information during projecttracking," Omega, Elsevier, vol. 39(4), pages 416-426, August.
    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. Choi, Tsan-Ming & Ma, Cheng & Shen, Bin & Sun, Qi, 2019. "Optimal pricing in mass customization supply chains with risk-averse agents and retail competition," Omega, Elsevier, vol. 88(C), pages 150-161.

    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. Way, Rupert & Lafond, François & Lillo, Fabrizio & Panchenko, Valentyn & Farmer, J. Doyne, 2019. "Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 211-238.
    2. Mazzola, Joseph B. & Neebe, Alan W. & Rump, Christopher M., 1998. "Multiproduct production planning in the presence of work-force learning," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 336-356, April.
    3. Sun, Xiaojie & Tang, Wansheng & Zhang, Jianxiong & Chen, Jing, 2021. "The impact of quantity-based cost decline on supplier encroachment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    4. Ben Klemens, 2021. "Attributing Value to Patents and Trademarks in Complex Production Chains," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 842-875, June.
    5. O. Zeynep Akşin, 2007. "On valuing appreciating human assets in services," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(2), pages 221-235, March.
    6. Vanhoucke, Mario & Colin, Jeroen, 2016. "On the use of multivariate regression methods for longest path calculations from earned value management observations," Omega, Elsevier, vol. 61(C), pages 127-140.
    7. Martens, Annelies & Vanhoucke, Mario, 2019. "The impact of applying effort to reduce activity variability on the project time and cost performance," European Journal of Operational Research, Elsevier, vol. 277(2), pages 442-453.
    8. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2022. "Using Earned Value Management and Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 297(2), pages 451-466.
    9. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2020. "The impact of a limited budget on the corrective action taking process," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1070-1086.
    10. 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.
    11. Wauters, Mathieu & Vanhoucke, Mario, 2017. "A Nearest Neighbour extension to project duration forecasting with Artificial Intelligence," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1097-1111.
    12. Yuchen Lin & Daxin Dong & Jiaxin Wang, 2021. "The Negative Impact of Uncertainty on R&D Investment: International Evidence," Sustainability, MDPI, vol. 13(5), pages 1-21, March.
    13. Lenah Cleo Kelepile, 2024. "A Comprehensive Analysis of Monitoring and Control Mechanisms in Operational Relocation Project at Limkokwing University, Botswana," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(5), pages 1759-1771, May.
    14. Alessandro Arlotto & Stephen E. Chick & Noah Gans, 2014. "Optimal Hiring and Retention Policies for Heterogeneous Workers Who Learn," Management Science, INFORMS, vol. 60(1), pages 110-129, January.
    15. Plaza, Malgorzata, 2016. "Balancing the costs of human resources on an ERP project," Omega, Elsevier, vol. 59(PB), pages 171-183.
    16. Martens, Annelies & Vanhoucke, Mario, 2017. "A buffer control method for top-down project control," European Journal of Operational Research, Elsevier, vol. 262(1), pages 274-286.
    17. Cohen, Izack & Iluz, Michal, 2015. "When cost–effective design strategies are not enough: Evidence from an experimental study on the role of redundant goals," Omega, Elsevier, vol. 56(C), pages 99-111.
    18. Cavagnini, Rossana & Hewitt, Mike & Maggioni, Francesca, 2020. "Workforce production planning under uncertain learning rates," International Journal of Production Economics, Elsevier, vol. 225(C).
    19. Basu, Arnab & Jain, Tarun & Hazra, Jishnu, 2018. "Supplier selection under production learning and process improvements," International Journal of Production Economics, Elsevier, vol. 204(C), pages 411-420.
    20. Gunasekaran, Angappa & Irani, Zahir & Choy, King-Lun & Filippi, Lionel & Papadopoulos, Thanos, 2015. "Performance measures and metrics in outsourcing decisions: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 161(C), pages 153-166.

    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:jomega:v:69:y:2017:i:c:p:29-42. 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/wps/find/journaldescription.cws_home/375/description#description .

    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.