Skip to main content
Log in

The incorporation of learning in production planning models

  • Chapter 4 Process Planning
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

Production managers employ numerous aggregate planning models to smooth work loads and minimize labor and inventory costs. Some of the more recently developed models incorporate the learning that occurs during repetitive work. This article discusses the history of both aggregate planning and learning models, the various combined models, and their appropriateness to a given environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. E.E. Adam, Jr. and R.J. Ebert,Production and Operations Management, 2nd Ed. (Prentice-Hall, Inc., Englewood Cliffs, N.J., 1982).

    Google Scholar 

  2. F.J. Andress, The learning curve as a production tool, Hvd. Bus. Rvw. 32, No. 1 (1954) 87.

    Google Scholar 

  3. D.D. Bedworth and J.E. Bailey,Integrated Production Control Systems (John Wiley & Sons, Inc., 1982).

  4. A.R. Behnezhad and B. Khoshnevis, The effects of manufacturing progress function on machine requirements and aggregate planning problems, TIMS/ORSA, Nov. 1985.

  5. E.H. Bowman, Production scheduling by the transportation method of linear programming, Op. Res. 4 (1956) 100.

    Google Scholar 

  6. J.R. Buck, J.M.A. Tanchoco and A.L. Sweet, Parameter estimation methods for discrete exponential learning curves, AIIE Trans. 8, no. 2 (1976) 184.

    Google Scholar 

  7. J.G.H. Carlson, Cubic learning curves: precision tool for labor estimating, Mfg. Engr. & Mgt. (Nov. 1973) 22.

  8. J.G. Carlson and Alan J. Rowe, How much does forgetting cost?, Industrial Engineering 8, no. 9 (1976) 40.

    Google Scholar 

  9. J.R. Crawford, Statistical accounting procedures in aircraft production, Aero Digest 44 (1944) 78.

    Google Scholar 

  10. E.B. Cochran, New concepts of the learning curve, J. Ind. Engr. 11, no. 4 (1960) 317.

    Google Scholar 

  11. E.B. Cochran,Planning Production Costs: Using the Improvement Curve (Chandler Publishing Company, San Francisco, 1968).

    Google Scholar 

  12. J.R. deJong, The effects of increasing skill on cycle time and its consequences for time standards, Ergonomics 1 (1957) 51.

    Google Scholar 

  13. R.J. Ebert, Time horizon: implications for aggregate scheduling effectiveness, AIIE Trans. 4, no. 4 (1972) 298.

    Google Scholar 

  14. R.J. Ebert, Aggregate planning with learning curve productivity, Mgt. Sci. 23, no. 2 (1976) 171.

    Google Scholar 

  15. S. Globerson, The deviation of actual performance around learning curve models, Int. J. Prod. Res. 22, no. 1 (1984) 51.

    Google Scholar 

  16. J.H. Glover, Manufacturing progress functions I. An alternative model and its comparison with existing functions, Int. J. Prod. Res., 4, no. 4 (1966A) 279.

    Google Scholar 

  17. J.H. Glover, Manufacturing progress functions II. Selection of trainees and control of their progress, Int. J. Prod. Res. 5, no. 1 (1966B) 43.

    Google Scholar 

  18. J.H. Glover, Manufacturing progress functions III. Production control of new products, Int. J. Prod. Res. 6, no. 1 (1967) 15.

    Google Scholar 

  19. F. Hanssmann and S.W. Hess, A linear programming approach to production and employment scheduling, Mgt. Tech. 1, no. 1 (1960) 46.

    Google Scholar 

  20. C.C. Holt, F. Modigliani and H.A. Simon, A linear decision rule for production and employment scheduling, Mgt. Sci. (Oct. 1955).

  21. C.C. Holt, F. Modigliani, J.F. Muth and H.A. Simon,Planning Production, Inventories and Work Force (Prentice-Hall, Inc., Englewood Cliffs, N.J., 1960).

    Google Scholar 

  22. F.C. Jelen and J.H. Black,Cost and Optimization Engineering, 2nd Ed. (McGraw-Hill Book Company, New York, 1983).

    Google Scholar 

  23. L.A. Johnson and D.C. Montgomery,Operations Research in Production Planning, Scheduling and Inventory Control (John Wiley & Sons, Inc., New York, 1974).

    Google Scholar 

  24. C.H. Jones, Parametric production planning, Mgt. Sci. 13, no. 11 (1967) 843.

    Google Scholar 

  25. R.S. Kaplan,Advanced Management Accounting (Prentice-Hall, Inc., Englewood Cliffs, N.J., 1982).

    Google Scholar 

  26. B. Khoshnevis and P.M. Wolfe, An aggregate production planning model incorporating dynamic productivity. Part I. Model development, IIE Trans. 15, no. 2 (1983A) 111.

    Google Scholar 

  27. B. Khoshnevis and P.M. Wolfe, An aggregate production planning model incorporating dynamic productivity. Part II. Solution methodology and analysis, IIE Trans. 15, no. 4 (1983B) 283.

    Google Scholar 

  28. B. Khoshnevis and P.M. Wolfe, A short-cycle product aggregate planning model incorporating improvement curve productivity, Engr. Costs and Prod. Econ. 10 (1986) 217.

    Google Scholar 

  29. G. Nadler and W.D. Smith, Manufacturing progress functions for types of processes, Int. J. Prod. Res. 2, no. 2 (1963) 115.

    Google Scholar 

  30. M.G. Orrbeck, D.R. Schuette and H.E. Thompson, The effect of worker productivity on production smoothing, Mgt. Sci. 14, no. 6 (1968) B-332.

    Google Scholar 

  31. C.C. Pegels, On start-up on learning curves: An expanded view, AIIE Trans. 1, no. 3 (1969) 216.

    Google Scholar 

  32. D. Sahal, A theory of progress functions, AIIE Trans. 11, no. 1 (1979) 23.

    Google Scholar 

  33. G.S. Snoddy, Learning and stability, Applied Psyc. 10 (1926) 1.

    Google Scholar 

  34. W.J. Stevenson,Production / Operations Management (Richard D. Irwin, Inc., Homewod, Ill., 1982).

    Google Scholar 

  35. D.R. Sule, The effect of alternate periods of learning and forgetting on economic manufacturing quantity, AIIE Trans. 10, no. 3 (1978) 38.

    Google Scholar 

  36. D.R. Sule, A note on production time variation in determing EMQ under influence of learning and forgetting, AIIE Trans. 13, no. 1 (1981) 91.

    Google Scholar 

  37. D.R. Sule, Effect of learning and forgetting on economic lot size scheduling problem, Int. J. Prod. Res. 21, no. 5 (1983) 771.

    Google Scholar 

  38. W.H. Taubert, A search decision rule for the aggregate scheduling problem, Mgt. Sci. 14, no. 6 (1968) B-343.

  39. M.S. Titleman, Learning curves — Key to better labor estimates, Product Engineering 29 (1957) 36.

    Google Scholar 

  40. E.A. Tunc and J. Haddock, A model for production and work force planning in long-cycle product environments, Tech. Rpt. 37-87-109, Decision Sci. & Engr. Systems, Rensselaer Polytechnic Inst., Troy, NY 12180-3590 (March 1987).

    Google Scholar 

  41. E.A. Tunc and J. Haddock, An optimization procedure and work force planning in long-cycle product environments, Tech. Rpt. 37-87-110, Decision Sci. & Engr. Systems, Rensselaer Polytechnic Inst., Troy, NY 12180-3590 (March 1987).

    Google Scholar 

  42. P.M. Wolfe, B. Khoshnevis, M.P. Terrell and R. Monjazeb, Aggregate planning models incorporate productivity — an overview, Proc. — 1979 spring annual conf., IIE, Atlanta (1979) 280.

  43. T.P. Wright, Factors affecting the cost of airplanes, J. Aeronautical Sci. 3, no. 2 (1936) 122.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kroll, D.E., Kumar, K.R. The incorporation of learning in production planning models. Ann Oper Res 17, 291–303 (1989). https://doi.org/10.1007/BF02096610

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02096610

Keywords

Navigation