Production planning and scheduling in multi-factory production networks: a systematic literature review

• Published in: International journal of production research 2021-04, Vol.59 (7), p.2028-2054
• Main Authors: Lohmer, Jacob, Lasch, Rainer
• Format: Article
• Language: English
• Subjects: Bibliometrics; distributed scheduling; Dynamic characteristics; Empirical analysis; Factories; Industrial plants; Industry 4.0; Literature reviews; multi-factory; Network analysis; Production planning; Production scheduling; Scheduling; systematic literature review
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2020.1797207

Multi-factory production planning and scheduling problems have been increasingly studied by scholars recently due to market uncertainty, technological trends like Industry 4.0 and increasing collaboration. Geographically dispersed factories may provide cost-saving potential and increase efficiency while also being subjected to varying capabilities and restrictions such as capacity constraints and labour costs. Traditional approaches in production planning and scheduling focus on the allocation of demand to a single factory and obtain sequences of operations on machines in this factory. In the multi-factory or distributed setting, an additional task includes assigning orders to potential factories beforehand. Starting with the first case studies in the late 1990s, research has increasingly been devoted to this research field and has considered numerous variations of the problem. We review 128 articles on multi-factory production planning and scheduling problems in this contribution and classify the literature according to shop configuration, network structure, objectives, and solution methods. Bibliometric analysis and network analysis are utilised to generate new findings. Research opportunities identified include integration with other planning stages, an investigation of key real-life objectives such as due date compliance and examining dynamic characteristics in the context of Industry 4.0. Besides, empirical studies are necessary to gain new practical insights.