Intelligent Production Logistics System Based on Internet of Things

  • Haiqin WangEmail author
  • Guangqiu Lu
  • Jiahui Liu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1117)


Internet of things technology is the basis of transformation and upgrading of manufacturing industry and it is also the basis of realization of intelligent manufacturing. The introduction of Internet of things technology in the production workshop can promote the transformation of manufacturing and logistics business models, as well as collaborative production scheduling and logistics scheduling. This paper discusses the goal setting of intelligent workshop production logistics system, the structure of intelligent workshop production logistics system and the key technologies to be solved in constructing intelligent workshop production logistics system. On this basis, the paper analyzes the characteristics of production logistics of tire enterprises, puts forward the train of thought of constructing intelligent production logistics system in rubber refining workshop, component workshop, molding workshop and vulcanization workshop of tire enterprises, and finally analyzes the expected effect. Intelligent workshop production logistics system can realize the integration of intelligent manufacturing and intelligent logistics, improve the production efficiency and logistics efficiency of manufacturing enterprises.


Internet of things Production logistics Intelligent manufacturing 



This research was supported by science and technology planning research of Qingdao Binhai University, design and application of automatic material handling system in tire enterprises, Project NO.: 2019KY03,2018/11/22


  1. 1.
    Ting, Q., Thurer, M., Wang, J., et al.: System dynamics analysis for an internet-of-things-enabled production logistics system. Int. J. Prod. Res. 55(9), 2622–2649 (2017)CrossRefGoogle Scholar
  2. 2.
    Huang, S., Guo, Y., Zha, S., et al.: An internet-of-things-based production logistics optimization method for discrete manufacturing. Int. J. Comput. Integr. Manuf. 32(1), 1–14 (2018)Google Scholar
  3. 3.
    Zhang, Y., Guo, Z., Lv, J., et al.: A framework for smart production-logistics systems based on CPS and industrial IoT. IEEE Trans. Ind. Inform. 14(9), 4019–4032 (2018)CrossRefGoogle Scholar
  4. 4.
    Ting, Q.U., Zhang, K., Luo, H., et al.: Internet-of-things based dynamic synchronization of production and logistics: mechanism, system and case study. J. Mech. Eng. 51(20), 36–44 (2015)CrossRefGoogle Scholar
  5. 5.
    Li, J.T., Yuan, H., Zhang, H.B.: Research on submerged logistics carrying AGV used in e-commerce distribution center. Appl. Mech. Mater. 722, 436–441 (2015)CrossRefGoogle Scholar
  6. 6.
    Wan, J., Tang, S., Hua, Q., et al.: Context-aware cloud robotics for material handling in cognitive industrial internet of things. IEEE Int. Things J. PP(99), 1 (2017)Google Scholar
  7. 7.
    Chang, F., Liu, X., Pei, J., et al.: Optimal production planning in a hybrid manufacturing and recovering system based on the internet of things with closed loop supply chains. Oper. Res. 16(3), 543–577 (2016)Google Scholar
  8. 8.
    Zhang, X., Zhou, H., Liu, G.S.: Design of the automatic guided vehicle control system applied to automotive logistics. Appl. Mech. Mater. 644–650, 381–384 (2014)Google Scholar
  9. 9.
    Aguilar, C.M., Sant Ana, C.T., Costa, A.G.V., et al.: Comparative effects of brown and golden flaxseeds on body composition, inflammation and bone remodelling biomarkers in perimenopausal overweight women. J. Funct. Foods 33, 166–175 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Qingdao Binhai UniversityQingdaoChina

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