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Flexible Services and Manufacturing Journal

, Volume 24, Issue 2, pp 119–141 | Cite as

Part feeding at high-variant mixed-model assembly lines

  • Jenny Golz
  • Rico Gujjula
  • Hans-Otto GüntherEmail author
  • Stefan Rinderer
  • Marcus Ziegler
Article

Abstract

The part feeding problem at automotive assembly plants deals with the timely supply of parts to the designated stations at the assembly line. According to the just-in-time principle, buffer storages at the line are frequently refilled with parts retrieved from a central storage area. In the industrial application at hand, this is accomplished by means of an internal shuttle system which supplies the various stations with the needed parts based on a given assembly sequence. The main objective is to minimize the required number of shuttle drivers. To solve this in-house transportation problem, a heuristic solution procedure is developed which is based on the decomposition of the entire planning problem into two stages. First, transportation orders are derived from the given assembly sequence. In the second stage, these orders are assigned to tours of the shuttle system taking transportation capacity restrictions, due dates and tour scheduling constraints into account. Numerical results show that the proposed heuristic solves even large-sized problem instances in short computational time. Benchmark comparisons with Kanban systems reveal the superiority of the proposed predictive part feeding approach.

Keywords

Part feeding Mixed-model assembly lines Tour-scheduling 

References

  1. Battini D, Faccio M, Persona A, Sgarbossa F (2009) Design of the optimal feeding policy in an assembly system. Int J Prod Econ 121:233–254CrossRefGoogle Scholar
  2. Boysen N, Bock S (2011) Scheduling just-in-time part supply for mixed-model assembly lines. Eur J Oper Res 21:15–25MathSciNetCrossRefGoogle Scholar
  3. Boysen N, Fliedner M, Scholl A (2008) Sequencing mixed-model assembly lines to minimize part inventory cost. OR Spec 30:611–633MathSciNetzbMATHCrossRefGoogle Scholar
  4. Boysen N, Fliedner M, Scholl A (2009a) Level scheduling of mixed-model assembly lines under storage constraints. Int J Prod Res 47:2669–2684zbMATHCrossRefGoogle Scholar
  5. Boysen N, Fliedner M, Scholl A (2009b) Production planning of mixed-model assembly lines: overview and extensions. Prod Plann Control 20:455–471CrossRefGoogle Scholar
  6. Boysen N, Fliedner M, Scholl A (2009c) Sequencing mixed-model assembly lines: survey, classification and model critique. Eur J Oper Res 192:349–373MathSciNetzbMATHCrossRefGoogle Scholar
  7. Boysen N, Fliedner M, Scholl A (2009d) Level scheduling for batched JIT supply. Flex Serv Manuf 21:31–50zbMATHCrossRefGoogle Scholar
  8. Bunte S, Kliewer N (2010) An overview on vehicle scheduling models. Public Transp 1:299–317CrossRefGoogle Scholar
  9. Choi W, Lee Y (2002) A dynamic part-feeding system for an automotive assembly line. Comp Ind Eng 43:123–134CrossRefGoogle Scholar
  10. Cieliebak M, Erlebach T, Hennecke F, Weber B, Widmayer P (2004) Scheduling with release times and deadlines on a minimum number of machines. In: Proceedings of the 3rd IFIP international conference on theoretical computer science. Kluwer, Toulouse, pp 209–222Google Scholar
  11. Clarke G, Wright JW (1964) Scheduling of vehicles from a central depot to a number of delivery points. Oper Res 12:568–581CrossRefGoogle Scholar
  12. Cordeau JF, Desaulniers G, Desrosiers J, Solomon MM, Soumis F (2002) The VRP with time windows. In: Toth P, Vigo D (eds) The vehicle routing problem. SIAM monographs on discrete mathematics and applications. SIAM, Philadelphia, pp 157–193Google Scholar
  13. Dantzig GB, Ramser JH (1959) The truck dispatching problem. Manag Sci 6:80–91MathSciNetzbMATHCrossRefGoogle Scholar
  14. de Souza MC, de Carvalho CR, Brizon WB (2008) Packing items to feed assembly lines. Eur J Oper Res 184:480–489zbMATHCrossRefGoogle Scholar
  15. Deechongkit S, Srinon R (2009) Three alternatives of material supply in assembly line: a comparative study. In: Oyabu T, Gen M (eds), Proceedings of Asia Pacific industrial engineering & management systems conference 2009 (APIEMS 2009), Kitakyushu, pp 2062–2069Google Scholar
  16. Desaulniers G, Desrosiers J, Ioachim I, Solomon MM, Soumis F, Villeneuve D (1998) A unified framework for deterministic time constrained vehicle routing and crew scheduling problems. In: Crainic TG, Laporte G (eds) Fleet management and logistics. Springer, Berlin, pp 57–93CrossRefGoogle Scholar
  17. Desrochers M, Lenstra JK, Savelsbergh MWP (1990) A classification scheme for vehicle routing and scheduling problems. Eur J Oper Res 46:322–332zbMATHCrossRefGoogle Scholar
  18. Emde S, Fliedner M, Boysen N (2011) Optimally loading tow trains for JIT-supply of mixed-model assembly lines. IIE Trans (to appear). doi: 10.1080/0740817X.2011.575442
  19. Gintner V, Kliewer N, Suhl L (2005) Solving large multiple-depot multiple-vehicle-type bus scheduling problems in practice. OR Spec 27:507–523zbMATHCrossRefGoogle Scholar
  20. Gujjula R, Werk S, Günther HO (2011) A heuristic based on Vogel’s approximation method for sequencing mixed-model assembly lines. Int J Prod Res 49(21):6451–6468CrossRefGoogle Scholar
  21. Inman RR, Bhaskaran S, Blumenfeld D (1997) In-plant material buffer sizes for pull system and level-material-shipping environments in the automotive industry. Int J Prod Res 35:1213–1228zbMATHCrossRefGoogle Scholar
  22. Klampfl E, Gusikhin O, Rossi G (2006) Optimization of workcell layouts in a mixed-model assembly line environment. Int J Flex Manuf Syst 17:277–299zbMATHGoogle Scholar
  23. Kotani S, Ito T, Ohno K (2004) Sequencing problem for a mixed-model assembly line in the Toyota production system. Int J Prod Res 42:4955–4974zbMATHCrossRefGoogle Scholar
  24. Laporte G (2009) Fifty years of vehicle routing. Transp Sci 43:408–416MathSciNetCrossRefGoogle Scholar
  25. Liu W, Han Y (2008) Car sequencing in mixed-model assembly lines from the perspective of logistics optimisation. In: Proceedings of the IEEE international conference on automation and logistics, Qingdao, pp 952–957. doi: 10.1109/ICAL.2008.4636287
  26. Löbel A (1998) Vehicle scheduling in public transit and lagrangean pricing. Manage Sci 44:1637–1649zbMATHCrossRefGoogle Scholar
  27. Malucelli F, Nicoloso S (2000) Shiftable interval graphs. In: Proceedings of the 6th international conference on graph theory. Marseille, pp 1–14Google Scholar
  28. Meyr H (2004) Supply chain planning in the German automotive industry. OR Spec 26:447–470zbMATHGoogle Scholar
  29. Pepin AS, Desualniers G, Hertz A, Huisman D (2008) A comparison of five heuristics for the multiple depot vehicle scheduling problem. J Sched 12:17–30CrossRefGoogle Scholar
  30. Ribeiro CC, Soumis F (1994) A column generation approach to the multiple-depot vehicle scheduling problem. Oper Res 42:41–52zbMATHCrossRefGoogle Scholar
  31. Röder A, Tibken B (2006) A methodology for modeling inter-company supply chains and for evaluating a method of integrated product and process documentation. Eur J Oper Res 169:1010–1029zbMATHCrossRefGoogle Scholar
  32. Şen A, Bülbül K (2008) A survey on multi trip vehicle routing problem. In: International logistics and supply chain congress 2008. IstanbulGoogle Scholar
  33. Solomon MM, Desrosiers J (1988) Time window constrained routing and scheduling problems. Transp Sci 22:1–13MathSciNetzbMATHCrossRefGoogle Scholar
  34. Vaidyanathan BS, Matson JO, Miller D, Matson JE (1999) A capacitated vehicle routing problem for just-in-time delivery. IIE Trans 31:1083–1092Google Scholar
  35. Yang L, Zhang X, Jiang M (2009) An optimal kanban system in a multi-stage, mixed-model assembly line. J Syst Sci Syst Eng 19:36–49CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jenny Golz
    • 1
  • Rico Gujjula
    • 2
  • Hans-Otto Günther
    • 2
    Email author
  • Stefan Rinderer
    • 1
  • Marcus Ziegler
    • 1
  1. 1.Daimler AGUlmGermany
  2. 2.Department of Production ManagementTechnical University of BerlinBerlinGermany

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