Author
Abstract
Nowadays, many companies have several plants as a result of acquisitions or mergers, i.e. horizontal integration. A similar situation occurs with groups of companies which maintain their original brands but have centralized their manufacturing operations. This leads to the same kind of product being manufactured in different plants or under different brand names. In the context of a methodology for the redesign of supply chains, this tool evaluates the synergistic manufacturing in the chains and the minimum costs. The presented linear programs analyse how a better assignment of products to plants can be achieved in terms of costs, according to the resources used, while simultaneously improving the synergistic indicators. Two optimization models are proposed: the first, to obtain the best configuration at a given time, and the second, to manage the manufacturing of car models during several years. The case study is set in the automotive sector, using data from a group of companies with several brands. The application shows that the various plants have common resources, and synergies are feasible. This is justified after evaluating the costs, according to the resources needed. The new assignment of car models to plants takes these synergies into account and the new resource requirements are defined, also considering synergies. In the case study the best decisions in cost for some synergy levels in 10 years are determined. The results show that good synergy levels can be achieved with acceptable increases in costs.
Suggested Citation
Nicolas Anich & Manuel Mateo-Doll, 2025.
"Manufacturing synergies in the redesign of multi-business supply chains through linear programming to meet the evolution of demand,"
Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 33(4), pages 1251-1281, December.
Handle:
RePEc:spr:cejnor:v:33:y:2025:i:4:d:10.1007_s10100-024-00918-z
DOI: 10.1007/s10100-024-00918-z
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