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On a learning precedence graph concept for the automotive industry

Author

Listed:
  • Hanne Klindworth
  • Christian Otto

    () (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

  • Armin Scholl

    () (School of Economics and Business Administration, Friedrich-Schiller-University Jena)

Abstract

Assembly line balancing problems (ALBP) consist in assigning the total workload for manufacturing a product to stations of an assembly line as typically applied in automotive industry. The distribution of the tasks to the stations is due to restrictions which can be expressed in a precedence graph. However, automotive manufacturers usually do not know complete precedence graphs describing the production processes of their models. Unfortunately, the known approaches for graph generation are not suitable for the conditions in the automotive industry. We describe a new graph generation approach that is based on learning from past production sequences and forms a sufficient precedence graph. This graph, indeed, restricts the ALBP instance but guarantees feasible line balances. Computational experiments indicate that the proposed procedure is able to approximate the real precedence graph sufficiently well to detect optimal or nearly optimal solutions for all instances of a benchmark data set. So, the new approach is applicable and effective and might be a major step to close the gap between theoretical line balancing research and practice of assembly line planning.

Suggested Citation

  • Hanne Klindworth & Christian Otto & Armin Scholl, 2010. "On a learning precedence graph concept for the automotive industry," Jena Research Papers in Business and Economics - Working and Discussion Papers (Expired!) 09/2010, Friedrich-Schiller-University Jena, School of Economics and Business Administration.
  • Handle: RePEc:jen:jenjbe:2010-09
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    File URL: http://dx.doi.org/10.1016/j.ejor.2011.09.024
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    References listed on IDEAS

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    1. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2007. "A classification of assembly line balancing problems," European Journal of Operational Research, Elsevier, vol. 183(2), pages 674-693, December.
    2. Anthony A. Mastor, 1970. "An Experimental Investigation and Comparative Evaluation of Production Line Balancing Techniques," Management Science, INFORMS, vol. 16(11), pages 728-746, July.
    3. Scholl, Armin & Becker, Christian, 2006. "State-of-the-art exact and heuristic solution procedures for simple assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 666-693, February.
    4. Becker, Christian & Scholl, Armin, 2006. "A survey on problems and methods in generalized assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 694-715, February.
    5. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2008. "Assembly line balancing: Which model to use when," International Journal of Production Economics, Elsevier, vol. 111(2), pages 509-528, February.
    6. Scholl, Armin, 1995. "Balancing and sequencing of assembly lines," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 9690, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Becker, Christian & Scholl, Armin, 2009. "Balancing assembly lines with variable parallel workplaces: Problem definition and effective solution procedure," European Journal of Operational Research, Elsevier, vol. 199(2), pages 359-374, December.
    8. Scholl, Armin & Klein, Robert, 1997. "SALOME. a bidirectional branch and bound procedure for assembly line balancing," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 7890, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Scholl, Armin & Fliedner, Malte & Boysen, Nils, 2010. "Absalom: Balancing assembly lines with assignment restrictions," European Journal of Operational Research, Elsevier, vol. 200(3), pages 688-701, February.
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    Cited by:

    1. Otto, Christian & Otto, Alena, 2014. "Multiple-source learning precedence graph concept for the automotive industry," European Journal of Operational Research, Elsevier, vol. 234(1), pages 253-265.
    2. Sternatz, Johannes, 2014. "Enhanced multi-Hoffmann heuristic for efficiently solving real-world assembly line balancing problems in automotive industry," European Journal of Operational Research, Elsevier, vol. 235(3), pages 740-754.
    3. Otto, Alena & Otto, Christian & Scholl, Armin, 2013. "Systematic data generation and test design for solution algorithms on the example of SALBPGen for assembly line balancing," European Journal of Operational Research, Elsevier, vol. 228(1), pages 33-45.

    More about this item

    Keywords

    assembly; line balancing; auto industry; manufacturing process; precedence graph; learning approach; decision support;

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