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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    5. 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.
    6. Ronald J. Ebert, 1976. "Aggregate Planning with Learning Curve Productivity," Management Science, INFORMS, vol. 23(2), pages 171-182, October.
    7. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-1064, September.
    8. 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.
    9. 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.
    10. Allen C. Miller, III & Thomas R. Rice, 1983. "Discrete Approximations of Probability Distributions," Management Science, INFORMS, vol. 29(3), pages 352-362, March.
    11. 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.
    12. Norman Keith Womer, 1979. "Learning Curves, Production Rate, and Program Costs," Management Science, INFORMS, vol. 25(4), pages 312-319, April.
    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.
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    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.

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