The intelligent production line configuration strategy
Establishing an intelligent production line with high flexibility entails significant expenses, thereby strategic decision-making regarding the utilization of labor flexibility in the production line configuration becomes crucial for the success of a smart factory. This study considers two predominant production line configuration strategies in a production environment characterized by multi-variety and small-batch orders: (1) a double-line configuration strategy , where a fully automated intelligent production line focuses on producing relatively standardized products, while a manual production line is dedicated to crafting personalized products. We obtain optimal work allocation under this strategy. (2) a line-changeover configuration strategy , characterized by a single flexible production line where machine-driven tasks are automatically executed. Manual intervention is only required during line changeovers and setups between different product types. A comparative cost analysis between these two configuration strategies reveals that, for production batch size exceeding a batch threshold, the line-changeover strategy outperforms the double-line strategy. Moreover, if a square root rule is satisfied, the line-changeover strategy consistently outperforms the double-line strategy. Notably, investments directed towards setup reduction prove instrumental in reducing production costs and reducing the batch threshold, thereby amplifying the advantages of the line-changeover strategy. The future comparative advantage of these two configuration strategies is contingent upon ongoing technological developments. • This study compares two production line configuration strategies—double-line configuration (DLC) and line-changeover configuration (LCC). • The DLC strategy optimally allocates work between a fully automated intelligent production line and a manual line. • The LCC strategy outperforms the DLC strategy when batch size exceeds a critical threshold. • Investments in setup reduction significantly enhance the cost-efficiency of the LCC strategy, reducing the batch threshold.
Authors
- Yanyu Zhang (ORCID: https://orcid.org/0000-0001-7081-637X)
- Hui Wang (ORCID: https://orcid.org/0000-0001-8213-1626)
- Guohui Chen (ORCID: https://orcid.org/0000-0003-0657-8121)
- Qiguo Gong (ORCID: https://orcid.org/0000-0002-7783-9467)
Institutions
- Chongqing Technology and Business University (CN)
- National Marine Environmental Forecasting Center (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- International Journal of Production Economics
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1016/j.ijpe.2025.109647
- Citations
- 6
- Primary Topic
- Scheduling and Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 7.45
Funders
- National Natural Science Foundation of China