Integer programming models versus advanced planning business software for a multi-level mixed-model assembly line problem

Tobias Kreiter () and Ulrich Pferschy ()
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Tobias Kreiter: University of Graz
Ulrich Pferschy: University of Graz

Central European Journal of Operations Research, 2020, vol. 28, issue 3, No 13, 1177 pages

Abstract: Abstract Many manufactures are shifting from classical production environments with large batch sizes towards mixed-model assembly lines due to increasing product variations and highly individual customer requests. However, an assembly line should still be run with constant speed and cycle time. Clearly, the consecutive production of different models will cause a highly unbalanced temporal distribution of workload. This can be avoided by moving some assembly steps to pre-levels thus smoothing out the utilization of the main line. In the resulting multi-level assembly line the sequencing decision on the main line has to take into account the balancing of workload for all pre-levels. Otherwise, the modules or parts delivered from the pre-levels would cause congestion of the main line. One planning strategy aims at mixing the models on the main line to avoid blocks of identical units. In this contribution we compare two different realizations for this approach. On one hand we present a mixed-integer programming model (MIP), strengthen it by adding valid inequalities and enrich it with a number of relevant practical extensions. Also the actual objective of explicitly balancing pre-level workloads is considered. On the other hand, we illustrate how this strategy could be realized in an advanced planning system linked to an enterprise resource planning system, namely SAP APO. Finally, we perform a computational study to investigate the possibilities and limitations of MIP models and the realization in SAP APO. The experiments rely on a real-world production planning problem of a company producing engines and gearboxes.

Keywords: Multi-level production system; Load balancing; Model-mix planning; Mixed-integer programming; SAP APO (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10100-019-00642-z

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