Abstract

The Industrial Internet of Things (IIoT) enables the improvement of the productivity and intelligent level of factory. The procedure of product quality inspection has generally adopted machine intelligence algorithms instead of manual operation to improve efficiency. In this paper, we propose a product quality inspection system scheme based on software-defined edge intelligent controller (SD-EIC). By adopting the software definition and resource virtualization technologies, the hardware platform of SD-EIC is designed to support the real-time control tasks and non-real-time edge computing tasks at the same time. To this end, we propose the scheme and architecture of product quality inspection system based on SD-EIC. Multiple virtual controllers and virtual edge computing nodes are constructed on a set of SD-EIC hardware platform to realize the integrated deployment of the real-time control for terminal devices and the AI model reasoning of product defect recognition algorithm based on machine vision respectively. In addition, the management and control scheme of product quality inspection system based on industrial information model is proposed. By constructing the semantic-based digital twin information model of terminal device, the flexible adjustment and parameter configuration of terminal device are realized to meet the demands of flexible production and manufacturing. The proposed product quality inspection system solution can effectively improve the utilization of hardware resources and the efficiency of product quality inspection, and reduce the overall deployment cost of the system. It can flexibly adapt to product diversity and different industrial scenarios.

Details

Title
The product quality inspection scheme based on software-defined edge intelligent controller in industrial internet of things
Author
Hu, Pengfei 1 ; He, Chunming 2 ; Zhu, Yiming 3 ; Li, Tianhui 1 

 HollySys Group Co., Ltd., Central Research Institute, Beijing, China; Beijing HollySys Co., Ltd., Beijing, China 
 HollySys Group Co., Ltd., Beijing, China 
 HollySys Group Co., Ltd., Central Research Institute, Beijing, China 
Pages
113
Publication year
2023
Publication date
Dec 2023
Publisher
Springer Nature B.V.
e-ISSN
2192113X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2842699644
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.