Application exploration of digital twin technology in petrochemical industry

被引:0
|
作者
Yu B. [1 ]
Zhu W. [2 ]
机构
[1] Hengli Petrochemical Company Ltd, Liaoning, Dalian
[2] Beijing Seatone Scisence and Technology Development Company, Beijing
关键词
data; digital twin; digital twin model; digital twin system; petroleum refining and chemical industry;
D O I
10.16085/j.issn.1000-6613.2019-1205
中图分类号
学科分类号
摘要
As one of the important energy sources in China, petroleum refining and chemical industry is an important basis for the development of national economy. To ensure the safe and efficient production of oil refining and chemical is our important goal. In view of the petroleum and petrochemical process industry conditions that exists in the continuity of the production process, the problem of complicated variety, the technology of digital twin was introduced in the enterprise. Through the build process industry of digital twin physical model, the working condition of the twin model, the enterprise set up digital twin system, in order to improve the efficiency of enterprise production, to ensure safe and efficient operation. The paper explores the process of twin system based on digital industry of digital twin physical model, the working condition of the twin model application, in order to achieve optimal control of production, product quality control and high value of application, improve the efficiency of production, ensure the efficient operation of the factory. © 2019, Chemical Industry Press Co., Ltd.. All rights reserved.
引用
收藏
页码:278 / 281
页数:3
相关论文
共 11 条
  • [1] ZHOU Yanhong, WANG Baicun, Toward new-generation intelligent manufacturing[J], Engineering, 4, 1, pp. 11-20, (2018)
  • [2] ZANG Jiyuan, WANG Baicun, MENG Liu, Et al., Brief analysis on three basic paradigms of intelligent manufacturing[J], Engineering Science, 20, 4, pp. 13-18, (2018)
  • [3] SHI Yiwen, CAI Zhongyao, Construction of water conservancy project operation management system based on digital twin technology, 7th Water Conservancy Information Technology Forum 2019, (2019)
  • [4] GRIEVES M, VICKERS J., Digital twin: mitigating unpredictable, undersirable emergent behavior in complex system, (2017)
  • [5] TAO Fei, ZHANG Meng, CHENG Jiangfeng, Et al., Digital twin workshop: a new paradigm for future workshop[J], Computer Integrated Manufacturing Systems, 23, 1, pp. 1-9, (2017)
  • [6] TAO F, ZHANG M, NEE A., Digital twin driven smart manufacturing, (2019)
  • [7] FEI T, CHENG J, QI Q, Et al., Digital twin-driven product design, manufacturing and service with big data[J], International Journal of Advanced Manufacturing Technology, 94, 4, pp. 3563-3576, (2017)
  • [8] TAO Fei, LIU Weiran, ZHANG Meng, Et al., Digital twin five-dimensional model and ten field applications[J], Computer Integrated Manufacturing Systems, 25, 1, pp. 1-18, (2019)
  • [9] ZHUANG Cunbo, LIU Jianhua, XIONG Hui, Et al., Connotation, architecture and trends of product digital twin[J], Computer Integrated Manufacturing Systems, 23, 4, pp. 753-768, (2017)
  • [10] SOLIDWORKS mechanical conceptual based on 3D experience of Dassault Systèmes, Aeronautical Manufacturing Technology, 4, (2014)