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The intelligent production line configuration strategy

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  • Gong, Qiguo
  • Zhang, Yanyu
  • Chen, Guohui
  • Wang, Hui

Abstract

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.

Suggested Citation

  • Gong, Qiguo & Zhang, Yanyu & Chen, Guohui & Wang, Hui, 2025. "The intelligent production line configuration strategy," International Journal of Production Economics, Elsevier, vol. 285(C).
  • Handle: RePEc:eee:proeco:v:285:y:2025:i:c:s092552732500132x
    DOI: 10.1016/j.ijpe.2025.109647
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