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The Effects of Worker Learning, Forgetting, and Heterogeneity on Assembly Line Productivity

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Author Info

  • Scott M. Shafer

    ()
    (Babcock Graduate School of Management, Wake Forest University, P.O. Box 7659, Winston-Salem, North Carolina 27109-7659)

  • David A. Nembhard

    ()
    (Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Avenue, Madison, Wisconsin 53706-1572)

  • Mustafa V. Uzumeri

    ()
    (Department of Management, Auburn University, 415 W. Magnolia Avenue, Auburn, Alabama 36849-5241)

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    Abstract

    The authors investigate through several simulations how patterns of learning and forgetting affect the operating performance of an assembly line. A unique aspect of this study is that a distribution of learning/forgetting behavior based on an empirical population of workers is used rather than assuming the same learning pattern for all employees. The paper demonstrates that modeling only central tendency and not the variations across workers tends to systematically underestimate overall productivity. The data used to estimate the parameters for the distribution of learning curves were collected from an assembly line that produces car radios. Analysis of the models fit to a population of workers reveals that higher levels of previous experience are positively correlated with higher steady-state productivity levels and negatively correlated with the learning rate. To further motivate the study, a conceptual model with several factors hypothesized to influence assembly line productivity is presented. Among key factors included in the model are the rate of worker learning, the size of the worker pool, task tenure, and the magnitude of worker forgetting. In controlled computer simulation experiments, each of these factors was found to be statistically significant, as were a number of the two-way interaction terms.

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    File URL: http://dx.doi.org/10.1287/mnsc.47.12.1639.10236
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 47 (2001)
    Issue (Month): 12 (December)
    Pages: 1639-1653

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    Handle: RePEc:inm:ormnsc:v:47:y:2001:i:12:p:1639-1653

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    Related research

    Keywords: Learning; Forgetting; Worker Heterogeneity; Simulation;

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    Cited by:
    1. Luca Colombo & Paola Labrecciosa, 2012. "Inter-firm knowledge diffusion, market power, and welfare," Journal of Evolutionary Economics, Springer, vol. 22(5), pages 1009-1027, November.
    2. David Besanko & Ulrich Doraszelski & Yaroslav Kryukov & Mark Satterthwaite, 2008. "Learning-by-Doing, Organizational Forgetting, and Industry Dynamics," GSIA Working Papers 2009-E22, Carnegie Mellon University, Tepper School of Business.
    3. Heimeriks, K.H. & Duysters, G.M., 2003. "Alliance capability as mediator between experience and alliance performance: an empirical investigation into the alliance capability development process," Working Papers 03.18, Eindhoven Center for Innovation Studies.
    4. Gnanlet, Adelina & Gilland, Wendell G., 2014. "Impact of productivity on cross-training configurations and optimal staffing decisions in hospitals," European Journal of Operational Research, Elsevier, vol. 238(1), pages 254-269.
    5. Jason Hockenberry & Lorens Helmchen, 2014. "The Nature of Surgeon Human Capital Depreciation," NBER Working Papers 20017, National Bureau of Economic Research, Inc.
    6. Corominas, Albert & Olivella, Jordi & Pastor, Rafael, 2010. "A model for the assignment of a set of tasks when work performance depends on experience of all tasks involved," International Journal of Production Economics, Elsevier, vol. 126(2), pages 335-340, August.
    7. Sayin, Serpil & Karabati, Selcuk, 2007. "Assigning cross-trained workers to departments: A two-stage optimization model to maximize utility and skill improvement," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1643-1658, February.

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