Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 14, Issue 9, Pages 4019-4032Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2018.2845683
Keywords
Analytical target cascading; cyber-physical systems (CPSs); industrial internet of things (IIoT); production-logistics; self-organizing configuration
Categories
Funding
- National Science Foundation of China [51675441]
- Fundamental Research Funds for the Central Universities [3102017jc04001]
- 111 Project Grant of NPU [B13044]
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Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems.
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