Advertisement

OR Spectrum

, Volume 35, Issue 1, pp 251–290 | Cite as

Lead time anticipation in Supply Chain Operations Planning

  • Michiel M. JansenEmail author
  • Ton G. de Kok
  • Jan C. Fransoo
Open Access
Regular Article

Abstract

Linear programming (LP) models for Supply Chain Operations Planning are widely used in Advanced Planning Systems. The solution to the LP model is a proposal for order releases to the various production units (PU) in the supply network. There is a non-linear relationship between the work-in-process in the PU and the lead time that is difficult to capture in the LP model formulation. We propose a two-step lead time anticipation (LTA) procedure where the LP model is first solved irrespective of the available production capacity and is subsequently updated with aggregate order release targets. The order release targets are generated by a local smoothing algorithm that accounts for the evolution of the stochastic workload in the PU. A solution that is both feasible with respect to the planned lead time and meets the material requirements may not exist. By means of discrete event simulation, we compare a conservative strategy where the production quantities are reduced to an optimistic strategy where the planned lead time constraint is allowed to be violated.

Keywords

Supply chain management Hierarchical production planning Lead time anticipation Production smoothing 

Notes

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

References

  1. Asmundsson J, Rardin RL, Uzsoy R (2006) Tractable nonlinear production planning models for semiconductor wafer fabrication facilities. IEEE Trans Semicond Manuf 19(1): 95–111CrossRefGoogle Scholar
  2. Asmundsson J, Rardin RL, Turkseven CH, Uzsoy R (2009) Production planning with resources subject to congestion. Naval Res Logist 56(2): 142–157 ISSN:1520-6750CrossRefGoogle Scholar
  3. Bertrand JWM, Wortmann JC, Wijngaard J (1990) Production control: a structural and design oriented approach. Elsevier, AmsterdamGoogle Scholar
  4. Bitran GR, Tirupati D (1993) Hierarchical production planning. Handbooks in OR & MS, vol 4, chap 10. North-Holland, pp 523–568Google Scholar
  5. Byrne MD, Bakir MA (1999) Production planning using a hybrid simulation–analytical approach. Int J Prod Econ 59(1–3): 305–311CrossRefGoogle Scholar
  6. De Kok AG (1989) A moment-iteration method for approximating the waiting-time characteristics of the gi/g/1 queue. Probab Eng Inf Sci 3: 273–287CrossRefGoogle Scholar
  7. De Kok AG (2003) Evaluation and optimization of strongly ideal assemble-to-order systems. In: Shanthikumar JG, Yao, DD, Zijm WHM (eds) Stochastic modeling and optimization of manufacturing systems and supply chains, pp 203–242Google Scholar
  8. De Kok AG, Fransoo JC (2003) Planning supply chain operations: definition and comparison of planning concepts. In: Handbooks in operations research and management science, vol 11, pp 597–676. ISSN:0927-0507Google Scholar
  9. Graves SC (1986) A tactical planning model for a job shop. Oper Res 34(4): 522–533CrossRefGoogle Scholar
  10. Hackman ST, Leachman RC (1986) A general framework for modeling production. Manag Sci 35(4): 478–495CrossRefGoogle Scholar
  11. Hopp WJ, Spearman ML (2011) Factory physics. Irwin McGraw-HillGoogle Scholar
  12. Hung YF, Hou MC (2001) A production planning approach based on iterations of linear programming optimization and flow time prediction. J Chines Inst Ind Eng 18(3): 55–67Google Scholar
  13. Hung YF, Leachman RC (1996) A production planning methodology for semiconductor manufacturingbased on iterative simulation and linear programming calculations. IEEE Trans Semicond Manuf 9(2): 257–269CrossRefGoogle Scholar
  14. Hwang S, Uzsoy R (2005) A single stage multi-product dynamic lot sizing model with work in process and congestion. Technical report, Purdue UniversityGoogle Scholar
  15. Irdem DF, Kacar NB, Uzsoy R (2008) An experimental study of an iterative simulation-optimization algorithm for production planning. In: Proceedings of the 40th conference on winter simulation, pp 2176–2184Google Scholar
  16. Karmarkar US (1989) Capacity loading and release planning with work-in-progress (WIP) and leadtimes. J Manuf Oper Manag 2: 105–123Google Scholar
  17. Karmarkar US (1993) Logistics of production and inventory. In: Manufacturing lead times, order release and capacity loading, vol 4. North-Holland, pp 287–329Google Scholar
  18. Kim B, Kim S (2001) Extended model for a hybrid production planning approach. Int J Prod Econ 73(2): 165–173CrossRefGoogle Scholar
  19. Kohler-Gudum C, De Kok AG (2002) A safety stock adjustment procedure to enable target service levels in simulation of generic inventory systems. Technical report, Eindhoven University of TechnologyGoogle Scholar
  20. Law A (2007) Simulation modeling and analysis, 4th edn. McGraw-HillGoogle Scholar
  21. Meyr H, Wagner M, Rohde J (2005) Structure of advanced planning systems. Supply chain management and advanced planning, pp 109–115Google Scholar
  22. Missbauer H (2002) Aggregate order release planning for time-varying demand. Int J Prod Res 40(3): 699–718CrossRefGoogle Scholar
  23. Missbauer H (2009) Models of the transient behaviour of production units to optimize the aggregate material flow. Int J Prod Econ 118(2): 387–397CrossRefGoogle Scholar
  24. Missbauer H (2010) Order release planning with clearing functions: a queueing-theoretical analysis of the clearing function concept. Int J Prod Econ (in press)Google Scholar
  25. Pahl J, Voß S, Woodruff DL (2007) Production planning with load dependent lead times: an update of research. Ann Oper Res 153(1): 297–345 ISSN:0254-5330CrossRefGoogle Scholar
  26. Riano G (2002) Transient behavior of stochastic networks: application to production planning with load-dependent lead times. PhD thesis, Georgia Institute of TechnologyGoogle Scholar
  27. Schneeweiss C (2003) Distributed decision making, 2nd edn. Springer, BerlinCrossRefGoogle Scholar
  28. Selçuk B (2007) Dynamic performance of hierarchical planning systems: modeling and evaluation with dynamic planned lead times. PhD thesis, Eindhoven University of TechnologyGoogle Scholar
  29. Peterson R (1998) Inventory management and production planning and scheduling, 3rd edn. Wiley, New YorkGoogle Scholar
  30. Simpson NC (1999) Multiple level production planning in rolling horizon assembly environments. Eur J Oper Res 114(1): 15–28 ISSN:0377-2217CrossRefGoogle Scholar
  31. Spitter JM, Hurkens CAJ, De Kok AG, Lenstra JK, Negenman EG (2004) Linear programming models with planned lead times for supply chain operations planning. Eur J Oper Res 163: 706–720CrossRefGoogle Scholar
  32. Stadtler H (2005) Supply chain management and advanced planning—basics, overview and challenges. Eur J Oper Res 163(3): 575–588CrossRefGoogle Scholar
  33. van Houtum GJ (2006) Multiechelon production/inventory systems: optimal policies, heuristics, and algorithms. Tutorial in operations research, INFORMS 2006Google Scholar
  34. Vollmann TE, Berry WL, Whybark DC (1984) Manufacturing planning and control systems. Dow Jones-Irwin, HomewoodGoogle Scholar
  35. Zipkin PH (2000) Foundations of inventory management. McGraw-Hill, New YorkGoogle Scholar

Copyright information

© The Author(s) 2011

Authors and Affiliations

  • Michiel M. Jansen
    • 1
    Email author
  • Ton G. de Kok
    • 1
  • Jan C. Fransoo
    • 1
  1. 1.School of Industrial EngineeringEindhoven University of TechnologyEindhovenThe Netherlands

Personalised recommendations