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A Top-Down Approach for an Automatic Precedence Graph Construction under the Influence of High Product Variety

  • Simon Altemeier
  • Daniel Brodkorb
  • Wilhelm Dangelmaier
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 338)

Abstract

This paper describes a top-down method for an automatic precedence graph construction that can cope with high variant products. The concept generates a joint precedence graph including all variants of a product directly. The graph is automatically derived from the bill of materials and buildability rules as well as existing solutions for the assignment of tasks to workstations. The presented method is very error prone and can improve the practical applicability of many assembly line balancing problems, that could not be used in practice yet.

Keywords

Assembly Line Assembly Sequence Precedence Relation Assembly Line Balance Sequencing Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Boysen, N., Fliedner, M., Scholl, A.: Sequencing mixed-model assembly lines to minimize part inventory cost. OR Spectrum 192, 349–373 (2009)zbMATHMathSciNetGoogle Scholar
  2. 2.
    Scholl, A., Becker, C.: State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. Eur. Jour. of Operational Research 168, 666–693 (2006)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Bourjault, A.: Contribution a une Approch Methodology de L’assemblage Automatise: Elaboration Automatique des Sequences Operatoires. Universite de Franche-Comte (1984)Google Scholar
  4. 4.
    De Fazio, T.L., Whitney, D.E.: Simplified generation of all mechanical assembly sequences. IEEE Journal of Robotics and Automation RA-3(6), 640–658 (1987)CrossRefGoogle Scholar
  5. 5.
    Wilson, R.H.: Minimizing user queries in interactive assembly planning. IEEE Transactions on Robotics and Automation 11, 308–312 (1995)CrossRefGoogle Scholar
  6. 6.
    Jones, R.l.E., Wilson, R.H., Calton, T.L.: Constraintbased interactive assembly planning. In: Proc.: IEEE Int. Conf. on Robotics and Automation, vol. 1, pp. 913–920 (1997)Google Scholar
  7. 7.
    Kaufman, S.G., Wilson, R.H., Jones, R.E., Calton, T.L.: The archimedes 2 mechanical assembly planning system. In: Proc. IEEE Int. Conf. on Robotics and Automation, vol. 1, pp. 3361–3368 (1996)Google Scholar
  8. 8.
    Sanderson, A.C., Homem de Mello, L.S., Zhang, H.: Assembly sequence planning. AI Magazine 11, 62–81 (1990)Google Scholar
  9. 9.
    Santochi, M., Dini, G.: Computer-aided planning of assembly operations: the selection of assembly sequences. Robotics and Computer-Integrated Manufacturing 9, 439–446 (1992)Google Scholar
  10. 10.
    Yokota, Y., Rough, D.R.: Assembly/disassembly sequence planning. Assembly Automation 12, 31–38 (1992)CrossRefGoogle Scholar
  11. 11.
    Cho, Y., Shin, C.K., Cho, H.S.: Automated inference on stable robotics assembly sequences based upon the evaluation of base assembly motion instability. Robotica 11, 351–362 (1993)CrossRefGoogle Scholar
  12. 12.
    Domschke, W., Scholl, A., Vo, S.: Produktionsplanung. Springer, Heidelberg (1993)Google Scholar
  13. 13.
    Meyr, H.: Supply chain planning in the german automotive industry. OR Spectrum 26, 447–470 (2004)zbMATHCrossRefGoogle Scholar
  14. 14.
    Dangelmaier, W.: Produktion und Information-System und Modell. Springer, Heidelberg (2003)Google Scholar
  15. 15.
    Roeder, A.: A methodology for modeling inter-company supply chains and for evaluating a method of integrated product and process documentation. Eur. Jour. of Operational Research 169, 1010–1029 (2006)zbMATHCrossRefGoogle Scholar
  16. 16.
    Sinz, C.: Verifikation regelbasierter Konfigurationssysteme. Fak. fuer Informations- und Kognitionswissenschaften. Eberhard-Karls-Univ., Tuebingen (2003)Google Scholar
  17. 17.
    Boysen, N., Fliedner, M., Scholl, A.: Production planning of mixed-model assembly lines: Overview and extensions. Tech. rep., Friedrich-Schiller-University Jena (2007)Google Scholar
  18. 18.
    Chen, C.L.: Automatic assembly sequences generation by pattern-matching. Technical report, School of Engineering and Technology, Electrical Engineering and CAD/CAM Center, Purdue University (1989)Google Scholar
  19. 19.
    Jentsch, W., Kaden, F.: Automatic generation of assembly sequences. Artificial Intelligence and Information-Control Systems of Robots 1, 197–200 (1984)Google Scholar
  20. 20.
    Baldwin, D.F., Abell, T.E., Lui, M.-C., De Fazio, T.L., Whitney, D.E.: An integrated computer aid for generating and evaluating assembly sequences for mechanical products. IEEE Trans. Robot. and Automat. 7, 78–94 (1991)CrossRefGoogle Scholar
  21. 21.
    Henrioud, J.M., Bourjault, A.: LEGA - A computer-aided generator of assembly plans. In: Computer-Aided Mechanical Assembly Planning, pp. 191–215. Kluwer Academic Publishers, Dordrecht (1991)Google Scholar
  22. 22.
    Dini, G., Santochi, M.: Automated sequencing and subassembly detection in assembly planning. Annals CIRP 41, 1–4 (1992)CrossRefGoogle Scholar
  23. 23.
    Falkenauer, E.: Line balancing in the real world. In: Int. Conf. on Product Lifecycle Management (2005)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Simon Altemeier
    • 1
  • Daniel Brodkorb
    • 1
  • Wilhelm Dangelmaier
    • 1
  1. 1.Heinz Nixdorf InstituteUniversity of PaderbornPaderbornGermany

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