Advertisement

An approach for balancing and sequencing mixed-model JIT U-lines

  • Yakup Kara
  • Ugur Ozcan
  • Ahmet Peker
Original Article

Abstract

A successful implementation of a mixed-model U-line requires solutions for balancing and sequencing problems. This study proposes an approach for simultaneously solving the balancing and sequencing problems of mixed-model U-lines. The primary goal of the proposed approach is to minimize the number of workstations required on the line (Type I). To meet this aim, the proposed approach uses such a methodology that enables the minimization of the absolute deviation of workloads among workstations as well. In terms of minimizing the number of workstations required on the mixed-model U-line, as well as minimizing the absolute deviation of workloads among workstations, the proposed approach is the first method in the literature dealing with the balancing and sequencing problems of mixed-model U-lines. The newly developed neighborhood generation method employed in the simulated annealing (SA) method is another significant feature of the proposed approach. An illustrative example to clarify the solution methodology is presented. Some problem factors and algorithm parameters that may affect the performance of the approach are also tested by a comprehensive experimental study.

Keywords

Facilities planning and design Mixed-model production U-lines Simulated annealing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aarts E, Korst J (1989) Simulated annealing and Boltzman machines. Wiley, New YorkGoogle Scholar
  2. 2.
    Aase GR, Schniederjans MJ, Olson JR (2003) U-OPT: an analysis of exact U-shaped line balancing procedures. Int J Prod Res 41(17):4185–4210zbMATHCrossRefGoogle Scholar
  3. 3.
    Bard JF, Dar-El E, Shtub A (1992) An analytic framework for sequencing mixed model assembly lines. Int J Prod Res 30(1):35–48zbMATHGoogle Scholar
  4. 4.
    Baybars I (1986) A survey of exact algorithms for the simple line balancing problem. Manage Sci 32:909–932zbMATHMathSciNetGoogle Scholar
  5. 5.
    Bukchin J, Dar-El EM, Rubinovitz J (2002) Mixed model assembly line design in a make-to-order environment. Comput Ind Eng 41(4):405–421CrossRefGoogle Scholar
  6. 6.
    Dar-El EM, Cother RF (1975) Assembly line sequencing for model mix. Int J Prod Res 13(5):463–477Google Scholar
  7. 7.
    Duplaga EA, Bragg DJ (1998) Mixed-model assembly line sequencing heuristics for smoothing component parts usage: a comparative analysis. Int J Prod Res 36(8):2209–2224zbMATHCrossRefGoogle Scholar
  8. 8.
    Erel E, Sabuncuoglu I, Aksu BA (2001) Balancing of U-type assembly systems using simulated annealing. Int J Prod Res 39(13):3003–3015zbMATHCrossRefGoogle Scholar
  9. 9.
    Erel E, Sarin SC (1998) A survey of the assembly line balancing procedures. Prod Plan Control 9(5):414–434CrossRefGoogle Scholar
  10. 10.
    Ghosh S, Gagnon RJ (1989) A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. Int J Prod Res 27(4):637–670Google Scholar
  11. 11.
    Gokcen H, Erel E (1997) A goal programming approach to mixed-model assembly line balancing problem. Int J Prod Econ 48(2):177–185CrossRefGoogle Scholar
  12. 12.
    Hall R (1983) Zero inventories. American Production and Inventory Control Society/Dow Jones-Irwin, Homewood, IllinoisGoogle Scholar
  13. 13.
    Jin M, Wu SD (2002) A new heuristic method for mixed model assembly line balancing problem. Comput Ind Eng 44(1):159–169CrossRefGoogle Scholar
  14. 14.
    Karabati S, Sayin S (2003) Assembly line balancing in a mixed-model sequencing environment with synchronous transfers. Eur J Oper Res 149(2):417–429zbMATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Kim YK, Kim JY, Kim Y (2000) A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines. Appl Intell 13(3):247–258CrossRefGoogle Scholar
  16. 16.
    Kim YK, Kim SJ, Kim JY (2000) Balancing and sequencing mixed-model U-lines with a co-evolutionary algorithm. Prod Plan Control 11(8):754–764CrossRefGoogle Scholar
  17. 17.
    Kirkpatrick S, Gelatt CD, Veechi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680CrossRefMathSciNetGoogle Scholar
  18. 18.
    Macaskill JLC (1972) Production-line balances for mixed-model lines. Manage Sci 19(4):423–434zbMATHGoogle Scholar
  19. 19.
    Merengo C, Nava F, Pozzetti A (1999) Balancing and sequencing manual mixed-model assembly lines. Int J Prod Res 37(12):2835–2860zbMATHCrossRefGoogle Scholar
  20. 20.
    Miltenburg J (2002) Balancing and scheduling mixed-model U-shaped production lines. Int J Flex Manuf Syst 14(2):119–151CrossRefGoogle Scholar
  21. 21.
    Miltenburg J (2001) U-shaped production lines: a review of theory and practice. Int J Prod Econ 70:201–214CrossRefGoogle Scholar
  22. 22.
    Miltenburg J (1998) Balancing U-lines in a multiple U-line facility. Eur J Oper Res 109(1):1–23zbMATHCrossRefGoogle Scholar
  23. 23.
    Miltenburg J, Sparling D (1995) Optimal solution algorithms for the U-line balancing problem. Working paper, McMaster University, Hamilton, Ontario, CanadaGoogle Scholar
  24. 24.
    Miltenburg J, Sinnamon G (1995) Revisiting the mixed-model multi-level just-in-time scheduling problem. Int J Prod Res 33(7):2049–2052zbMATHGoogle Scholar
  25. 25.
    Miltenburg J, Wijngaard J (1994) The U-line balancing problem. Manage Sci 40(10):1378–1388zbMATHGoogle Scholar
  26. 26.
    Miltenburg J (1989) Level schedules for mixed-model assembly lines in just-in-time production systems. Manage Sci 35(2):192–207zbMATHGoogle Scholar
  27. 27.
    Miltenburg J, Sinnamon G (1989) Scheduling mixed model multi-level just-in-time production systems. Int J Prod Res 27(9):1487–1509Google Scholar
  28. 28.
    Miltenburg J, Sinnamon G (1992) Algorithms for scheduling multi-level just-in-time production systems. IIE Trans 24(2):121–130Google Scholar
  29. 29.
    Monden Y (1993) Toyota production system, 2nd edn. Engineering and Management Press, Norcross, GeorgiaGoogle Scholar
  30. 30.
    McMullen PR, Frazier GV (2000) A simulated annealing approach to mixed-model sequencing with multiple objectives on a just-in-time line. IIE Trans 32(8):679–686CrossRefGoogle Scholar
  31. 31.
    McMullen PR, Frazier GV (1998) Using simulated annealing to solve a multiobjective assembly line balancing problem with parallel workstations. Int J Prod Res 36(10):2717–2741zbMATHCrossRefGoogle Scholar
  32. 32.
    Salveson ME (1955) The assembly line balancing problem. J Ind Eng 6:18–25Google Scholar
  33. 33.
    Scholl A, Klein R (1999) ULINO: optimally balancing U-shaped JIT assembly lines. Int J Prod Res 37(4):721–736zbMATHCrossRefGoogle Scholar
  34. 34.
    Sparling D, Miltenburg J (1998) The mixed-model U-line balancing problem. Int J of Prod Res 36(2):485–501zbMATHCrossRefGoogle Scholar
  35. 35.
    Sridhar J, Rajendran C (1993) Scheduling in a cellular manufacturing system: a simulated annealing approach. Int J Prod Res 31:2927–2945Google Scholar
  36. 36.
    Talbot FB, Patterson H (1984) An integer programming algorithm with network cuts for solving the single model assembly line balancing problem. Manage Sci 30:85–99zbMATHGoogle Scholar
  37. 37.
    Thomopoulos NT (1970) Mixed model line balancing with smoothed station assignments. Manage Sci 16(9):593–603zbMATHGoogle Scholar
  38. 38.
    Thomopoulos NT (1967) Line balancing-sequencing for mixed-model assembly. Manage Sci 14(2):59–75Google Scholar
  39. 39.
    Urban TL (1998) Optimal balancing of U-shaped assembly lines. Manage Sci 44(5):738–741zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2006

Authors and Affiliations

  1. 1.Department of Industrial EngineeringSelcuk UniversityKonyaTurkey

Personalised recommendations