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Aggregate Planning with Learning Curve Productivity

Author

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  • Ronald J. Ebert

    (University of Missouri-Columbia)

Abstract

Research reports of others indicate that many manufacturing organizations experience (a) the probiem of aggregate planning, and (b) experience systematic productivity changes throughout the "life" of a product. Methods for resolving (a) and for quantifying (b) have been developed and applied independently in the operations management literature. All current aggregate planning models are suitable only for constant productivity situations. The current research integrates (a) and (b) into a single computer-based model which permits the development of aggregate-output plans in the face of changing, productivity. The model requires reformulation of traditional aggregate planning methods to incorporate changes in productivity and thereafter solves the reformulated planning problem using direct-computer search. The potential significance of the model is demonstrated by generating a series of aggregate plans for various learning rates. These plans are then used to develop manpower schedules, for cash flow analysis, and for making product pricing decisions.

Suggested Citation

  • Ronald J. Ebert, 1976. "Aggregate Planning with Learning Curve Productivity," Management Science, INFORMS, vol. 23(2), pages 171-182, October.
    • Handle: RePEc:inm:ormnsc:v:23:y:1976:i:2:p:171-182
    DOI: 10.1287/mnsc.23.2.171
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    Citations

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    Cited by:

    1. Michael J. Fry & Michael J. Magazine & Uday S. Rao, 2006. "Firefighter Staffing Including Temporary Absences and Wastage," Operations Research, INFORMS, vol. 54(2), pages 353-365, April.
    2. Manda, A.B. & Uzsoy, Reha, 2021. "Managing product transitions with learning and congestion effects," International Journal of Production Economics, Elsevier, vol. 239(C).
    3. 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.
    4. Noah Gans & Yong-Pin Zhou, 2002. "Managing Learning and Turnover in Employee Staffing," Operations Research, INFORMS, vol. 50(6), pages 991-1006, December.
    5. Chung‐Lun Li & Zhi‐Long Chen, 2006. "Bin‐packing problem with concave costs of bin utilization," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(4), pages 298-308, June.
    6. Gagnon, Roger J. & Sheu, Chwen, 2000. "The impact of learning, forgetting and capacity profiles on the acquisition of advanced technology," Omega, Elsevier, vol. 28(1), pages 51-76, February.
    7. Sanjeev Bordoloi, 2006. "A control rule for recruitment planning in engineering consultancy," Journal of Productivity Analysis, Springer, vol. 26(2), pages 147-163, October.
    8. Jennings, Mark G., 2013. "A smarter plan? A policy comparison between Great Britain and Ireland's deployment strategies for rolling out new metering technologies," Energy Policy, Elsevier, vol. 57(C), pages 462-468.
    9. 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.
    10. 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.
    11. Ngwenyama, Ojelanki & Guergachi, Aziz & McLaren, Tim, 2007. "Using the learning curve to maximize IT productivity: A decision analysis model for timing software upgrades," International Journal of Production Economics, Elsevier, vol. 105(2), pages 524-535, February.
    12. Onesun Steve Yoo & Guillaume Roels & Charles J. Corbett, 2016. "The Time–Money Trade-Off for Entrepreneurs: When to Hire the First Employee?," Manufacturing & Service Operations Management, INFORMS, vol. 18(4), pages 559-569, October.
    13. Anderson, Edward G., 2001. "Managing the impact of high market growth and learning on knowledge worker productivity and service quality," European Journal of Operational Research, Elsevier, vol. 134(3), pages 508-524, November.
    14. Bordoloi, Sanjeev K. & Matsuo, Hirofumi, 2001. "Human resource planning in knowledge-intensive operations: A model for learning with stochastic turnover," European Journal of Operational Research, Elsevier, vol. 130(1), pages 169-189, April.
    15. Fragnière, Emmanuel & Gondzio, Jacek & Yang, Xi, 2010. "Operations risk management by optimally planning the qualified workforce capacity," European Journal of Operational Research, Elsevier, vol. 202(2), pages 518-527, April.

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