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Logistics-aware manufacturing service collaboration optimisation towards industrial internet platform

Author

Listed:
  • Yulin Wang
  • Yongping Zhang
  • Fei Tao
  • Tingyu Chen
  • Ying Cheng
  • Shunkun Yang

Abstract

As a critical enabler for achieving smart manufacturing, the Industrial Internet platform aims to integrate distributed manufacturing services to complete complicated manufacturing tasks. Manufacturing service (MS) collaboration plays an important role in improving manufacturing efficiency and customers’ satisfaction and its optimisation is therefore of great significance. As MSs are geographically distributed, logistics is an essential ingredient that needs to be considered for MS collaboration optimisation. However, only straight-line logistics distances are considered in most of existing studies without considering effects of logistics route selection and complex geographical locations of MSs, thereby resulting in inaccuracy in practical applications. With the aim to overcome these drawbacks, this paper establishes an adjacent matrix-based logistics-aware MS collaboration optimisation (LA-MSCO) model with detailed definitions of time, cost and reliability attributes of logistics. An improved artificial bee colony algorithm with both dimensional self-adaptation and group leader mechanisms, i.e. DSA-GL-ABC, is proposed for solving the LA-MSCO problem. Simulation experiments indicate the better performance of DSA-GL-ABC algorithm in terms of searching capability, convergence speed and solution quality.

Suggested Citation

  • Yulin Wang & Yongping Zhang & Fei Tao & Tingyu Chen & Ying Cheng & Shunkun Yang, 2019. "Logistics-aware manufacturing service collaboration optimisation towards industrial internet platform," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 4007-4026, June.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:12:p:4007-4026
    DOI: 10.1080/00207543.2018.1543967
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    Cited by:

    1. Kamble, Sachin S. & Gunasekaran, Angappa & Ghadge, Abhijeet & Raut, Rakesh, 2020. "A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs- A review and empirical investigation," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Cheng, Lihong & Guo, Xiaolong & Li, Xiaoxiao & Yu, Yugang, 2022. "Data-driven ordering and transshipment decisions for online retailers and logistics service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    3. Ha, Seungyeon & Park, Yujun & Kim, Jongpyo & Kim, Seongcheol, 2023. "Research trends of digital platforms: A survey of the literature from 2018 to 2021," Telecommunications Policy, Elsevier, vol. 47(8).
    4. Wang Shijie & Zhang Yingfeng, 2021. "A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1091-1115, April.
    5. Lihua Jiang & Wei Chen & Shichang Lu & Zhaoxiang Chen, 2022. "Regulatory Effect on Information Sharing of Industrial Internet Platforms Based on Three Differentiated Game Scenarios," Sustainability, MDPI, vol. 15(1), pages 1-25, December.

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