Skip to main content

Load Dependent Lead Times — From Empirical Evidence to Mathematical Modeling

  • Chapter

Summary

As organizations move from creating plans for individual production lines to entire supply chains it is increasingly important to recognize that decisions concerning utilization of production resources impact the lead times that will be experienced. In this paper we give some insights into why this is the case by looking at the queuing that results in delays. In this respect, special mention should be made that it is difficult to experience related empirical data, especially for tactical planning issues. We use these insights to survey and suggest optimization models that take into account load dependent lead times and related “complications.”

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

5 References

  • Asmundsson, J., Rardin, R. L., Uzsoy, R. (2002): Tractable Nonlinear Capacity Models for Aggregate Production Planning, Working Paper, School of Industrial Engineering, Purdue University, West Lafayette.

    Google Scholar 

  • Asmundsson, J., Rardin, R. L., Uzsoy, R. (2003): An Experimental Comparison of Linear Programming Models for Production Planning Utilizing Fixed Lead Time & Clearing Functions, Working Paper, School of Industrial Engineering, Purdue University, West Lafayette.

    Google Scholar 

  • Buzacott, J. A., Shantikumar, J. G. (1993): Stochastic Models of Manufacturing Systems, Englewood Cliffs, New York.

    Google Scholar 

  • Caramanis, M. C., Ahn, O. M. (1999): Dynamic Lead Time Modeling for JIT Production Planning, Proceedings of the IEEE International Conference on Robotics and Automation, Detroit, MI, May 10–15, v2, 1450–1455.

    Google Scholar 

  • Chen, H., Harrison, M. J., Mandelbaum, A., van Ackere, A., Wein, L. M. (1988): Empirical Evaluation of a Queuing Network Model for Semiconductor Wafer Fabrication, Operations Research, 36(2): 202–215.

    Google Scholar 

  • Ettl, M., Feigin, G. E., Lin, G. Y., Yao, D. D. (2000): A Supply Network Model with Base-Stock Control and Service Requirements, Operations Research, 48(2): 216–232.

    Article  Google Scholar 

  • Graves, S. (1986): A Tactical Planning Model for Job Shops, Operations Research, 34(4): 522–533.

    MATH  Google Scholar 

  • Hackman, S. T., Leachman, R. C. (1989): A General Framework for Modeling Production, Management Science, 35(4): 478–495.

    Google Scholar 

  • Karmarkar, U. S. (1987): Lot Sizes, Lead Times and In-Process Inventories, Management Science, 33(3): 409–418.

    MathSciNet  MATH  Google Scholar 

  • Karmarkar, U. S. (1989): Capacity Loading and Release Planning with Work-In-Process (WIP) and Lead Times, Journal of Manufacturing and Operations Management, 2(2): 105–123.

    Google Scholar 

  • Karmarkar, U. S. (1993): Manufacturing Lead Times, Order Release and Capacity Loading, in: Graves, S., Rinnooy Kan, A., Zipkin, P. (eds.): Logistics of Production and Inventory, Handbooks in Operations Research and Management Science, Vol. 4, Amsterdam: p. 287–329.

    Google Scholar 

  • Karmarkar, U. S., Kekre, S., Kekre, S. (1985): Lotsizing in Multi-Item Multi Machine Job Shops, IIE Transactions, 17(3): 290–297.

    Google Scholar 

  • Lautenschläger, M. (1999): Mittelfristige Produktionsprogrammplanung mit auslastungsabhängigen Vorlaufzeiten (“Tactical Production Planning with Workload Dependent Forward Production Times”), PhD Thesis, TU Darmstadt.

    Google Scholar 

  • Missbauer, H. (1998): Bestandsregelung als Basis für eine Neugestaltung von PPSSystemen (“Inventory Control as a Basis for a New Concept for PPS-Systems”), Physica, Heidelberg.

    Google Scholar 

  • Spearman, M.L. (1991): An Analytic Congestion Model for Closed Production Systems with IFR Processing Times, Management Science, 37(8): 1015–1029.

    Article  MATH  Google Scholar 

  • Srinivasan, A., Carey, M., Morton, T. E. (1990): Resource Pricing and Aggregate Scheduling in Manufacturing Systems, Working Paper, GSIA, 1988 (Revised December 1990).

    Google Scholar 

  • Suri, R., Sanders, J.L. (1993): Performance Evaluation of Production Networks, in: Graves, S., Rinnooy Kan, A., Zipkin, P. (eds.): Logistics of Production and Inventory, Handbooks in Operations Research and Management Science, Vol. 4, Amsterdam: p. 199–286.

    Google Scholar 

  • Tatsiopoulos, I.P., Kingsman, B.G. (1983): Lead Time Management, European Journal of Operational Research, 14(4): 351–358.

    Article  Google Scholar 

  • Voß, S., Woodruff D.L. (2003): An Introduction to Computational Optimization Models for Production Planning in a Supply Chain, Springer, Berlin.

    Google Scholar 

  • Zäpfel, G., Missbauer, H. (1993): New Concepts for Production Planning and Control, European Journal of Operational Research, 67(3): 297–320.

    Google Scholar 

  • Zijm, W. H. M., Buitenhek, R. (1996): Capacity Planning and Lead Time Management, International Journal of Production Economics, 46–47: 165–179.

    Google Scholar 

  • Zipkin, P. H. (1986): Models for Design and Control of Stochastic, Multi-Item Batch Production Systems, Operations Research, 34(1): 91–104.

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Physica-Verlag Heidelberg

About this chapter

Cite this chapter

Pahl, J., Voß, S., Woodruff, D.L. (2005). Load Dependent Lead Times — From Empirical Evidence to Mathematical Modeling. In: Kotzab, H., Seuring, S., Müller, M., Reiner, G. (eds) Research Methodologies in Supply Chain Management. Physica-Verlag HD. https://doi.org/10.1007/3-7908-1636-1_35

Download citation

Publish with us

Policies and ethics