Cyclic Sequencing in Mixed-Model Production Systems

혼류 생산시스템의 주기적 생산순서

  • Choi, Wonjoon (Department of Industrial Engineering, University of Ulsan) ;
  • Kim, Yearnmin (Department of Industrial Engineering, University of Ulsan) ;
  • Park, Changkwon (Department of Industrial Engineering, University of Ulsan) ;
  • Lee, Yongil (Department of Industrial Engineering, University of Ulsan)
  • 최원준 (울산대학교 공과대학 산업정보경영공학부) ;
  • 김연민 (울산대학교 공과대학 산업정보경영공학부) ;
  • 박창권 (울산대학교 공과대학 산업정보경영공학부) ;
  • 이용일 (울산대학교 공과대학 산업정보경영공학부)
  • Published : 2004.12.31

Abstract

In mixed-model production systems, various models of products are produced alternately on the same production line. When the total number of models or the total production quantity is large, it takes a long time to determine the production sequence of the products. In this paper, we will show that in case of product rate variation problem (PRV) problem with nonidentical symmetric convex discrepancy function, an optimum sequence can be obtained by repeating an optimum sequence in a reduced subproblem.

Keywords

References

  1. Aigbedo, H. (2004), Analysis of Part Requirements Variance for a JIT Supply Chain, International Journal of Production Research, 42(2), 417-430 https://doi.org/10.1080/00207540310001614178
  2. Bautista, J., Companys, R., and Corominas, A. (1996), Heuristics and Exact Algorithms for Solving the Monden Problem, European Journal of Operational Research, 124,468-477
  3. Bautista, J., Companys, R., and Corominas, A. (2000), Note on Cyclic Sequences in the Product Rate Variation Problem, European Journal of Operational Research, 124, 468-477
  4. Duplaga, E.A. and Bragg, D.J. (1998), Mixed-Model Assembly Sequencing Heuristics for Smoothing Component Parts Usage: A Comparative Analysis, International Journal of Production Research, 36(8), 2209-2224 https://doi.org/10.1080/002075498192850
  5. Hyun, CJ., Kim, YK., and Kim, Y (1998), A Genetic Algorithm for. Multiple Objective Sequencing Problems in Mixed Model Assembly Lines, Computers & Operations Research, 25, 675-690
  6. Jin, M. and Wu, S.D. (2002), A New Heuristic Method for Mixed Model Assembly Line Balancing Problem, Computers & Industrial Engineering, 44,159-169
  7. Kubiak, W. (1993), Minimization of Production Rates in Just-In-Time Systems: A Survey, European Journal of Operational Research, 66, 259-271
  8. Kubiak, W. and Sethi,S.(1991), A Note on Level Schedules for Mixed-Model Assembly Lines in Just-In-Time Production Systems, Management Science, 37(1), 121-122 https://doi.org/10.1287/mnsc.37.1.121
  9. Miltenburg, J. (1989), Level Schedules for Mixed-Model Assembly Lines in Just-In-Time Production Systems, Management Science, 32(2), 192-207
  10. Miltenburg, J. and Goldstein, T. (1991), Developing Production Schedules with Balance Part Usage and Smooth Production Loads for Just-In-Time Production Systems, Naval Research Logistics, 38, 893-910
  11. Miltenburg, J. and Sinnamon,G.(1989), Scheduling Mixed- Model Multi-Level Just-In-Time Production Systems, International Journal of Production Research, 27, 1487-1509
  12. Miltenburg, J., Steiner, G., and Yeomans,S.(1990), A Dynamic Programming Algorithm for Scheduling Mized-Model, Just-InTime Production Systems, Mathematical Computing and Modeling, 13(3), 57-66 https://doi.org/10.1016/0895-7177(90)90370-3
  13. Monden, J. (1983), Toyota Production System, Institute of Industrial Engineers Press, Norcross, Georgia
  14. Papadimitriou, C.H. and Steiglitz, K. (1982), Combinatorial Optimization, Prentice-Hall, Inc., Englewood Cliffs, New Jersey
  15. Ponnambalam, S.G., Aravindan, P., and Rao, M.S. (2003), Genetic Algorithms for Sequencing Problems in Mixed Model Assembly Lines, 45, 669-690
  16. Steiner, G. and Yeomans, S. (1996), Optimal Level Schedules in Mixed-Model, Multi-Level JIT Assembly Systems with Pegging, European Journal of Operational Research, 95, 38-52
  17. Sumichrast, R.T. and Russell,R.S.(1990), Evaluating Mixed- Model Assembly Line Heuristics for Just-In-Time Production Systems, Journal of Operations Management, 9(3), 371-390 https://doi.org/10.1016/0272-6963(90)90161-6