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

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<b>.</b> 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.

近年来，受市场不确定性、工业4.0（Industry 4.0）等技术趋势以及协作需求持续深化的影响，多工厂生产规划与调度问题愈发受到学者们的关注。地理上分散布局的工厂虽具备节约成本、提升运营效率的潜力，但同时也面临各异的能力限制与约束条件，例如产能约束与人力成本差异。传统生产规划与调度方法多聚焦于将需求分配至单一工厂，并规划该工厂内机器上的作业工序序列。而在多工厂或分布式生产场景中，还需额外完成一项前置任务：预先将订单分配至候选工厂。自20世纪90年代末首批案例研究开展以来，该领域的相关研究不断增多，且已针对该问题衍生出诸多变体。本综述共梳理了128篇关于多工厂生产规划与调度问题的学术文献，并根据车间配置、网络结构、优化目标与求解方法四大维度对现有研究进行分类。研究采用文献计量分析与网络分析方法，挖掘出了全新的研究结论。本次综述识别出的未来研究方向包括：与其他规划阶段的集成研究、针对交付期合规等关键现实优化目标的探索，以及在工业4.0背景下对调度问题动态特性的分析。此外，为获取新的实践启示，还需开展更多实证研究。