A framework for smart production-logistics systems based on CPS and industrial IoT

Zhang, Y., Guo, Z., Lv, J. and Liu, Y. (2018) A framework for smart production-logistics systems based on CPS and industrial IoT. IEEE Transactions on Industrial Informatics, 14(9), pp. 4019-4032. (doi:10.1109/TII.2018.2845683)

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Abstract

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.

Item Type:Articles
Additional Information:This work was supported in part by the National Science Foundation of China under Grant 51675441, in part by the Fundamental Research Funds for the Central Universities under Grant 3102017jc04001, and in part by the 111 Project Grant of NPU under Grant B13044. Paper no. TII-17-2897.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Liu, Dr Ying
Authors: Zhang, Y., Guo, Z., Lv, J., and Liu, Y.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE Transactions on Industrial Informatics
Publisher:IEEE
ISSN:1551-3203
ISSN (Online):1941-0050
Published Online:08 June 2018
Copyright Holders:Copyright © 2018 IEEE
First Published:First published in IEEE Transactions on Industrial Informatics 14(9): 4019-4032
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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