Visual real-time monitoring method for discrete manufacturing workshop based on digital twin

被引：0
作者：
Wu P. [1 ]
Guo Y. [1 ]
Huang S. [1 ]
Yang N. [1 ]
Xiong W. [1 ]
Guo J. [2 ]
机构：
[1] College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing
[2] Shanghai Spaceflight Precision Machinery Instutute, Shanghai
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2021年 / 27卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Aerospace products; Digital twin; Discrete manufacturing; Modeling; Real time monitoring;
D O I：
10.13196/j.cims.2021.06.007
中图分类号：
学科分类号：
摘要：
Focusing on the problems of real-time monitoring, poor control ability and opaque management in discrete manufacturing workshop, an object-oriented method was proposed to realize a real-time monitoring method for discrete manufacturing workshops based on Digital Twin (DT). DT-based visual real-time monitoring method architecture for discrete manufacturing workshop was built, and its key implementation process was clarified. Four key technologies to realize real-time monitoring based on DT were described in detail, including data modeling and transmission method based on AutomationML and OPC UA, event-driven virtual and real mapping method, workshop logic modeling method based on complex event processing, information visualization and push. Taking an aerospace product machining workshop as an application case, the effectiveness of the monitoring method was verified by combining the actual production process and the developed prototype system. © 2021, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：1605 / 1616
页数：11
相关论文
共 22 条
  • [1] GRIEVES M., Digital twin: Manufacturing excellence through virtual factory replication, (2014)
  • [2] HUANG Shaohua, GUO Yu, ZHA Shanshan, Et al., Review on Internet-of-Manufacturing-Things and key technologies for discrete workshop, Computer Integrated Manufacturing Systems, 25, 2, pp. 284-302, (2019)
  • [3] NORD J H, KOOHANG A, PALISZKIEWICZ J., The Internet of Things: Review and theoretical framework, Expert Systems with Applications, 133, 1, pp. 97-108, (2019)
  • [4] LIU Mingzhou, WANG Qiang, MA Jing, Visual monitoring platform of manufacturing process based on real-time information driven, China Mechanical Engineering, 26, 18, pp. 2466-2472, (2015)
  • [5] SCHROEDER G N, STEINMETZ C, PEREIRA C E, Et al., Digital twin data modeling with automationml and a communication methodology for data exchange, IFAC-Papers OnLine, 49, 30, pp. 12-17, (2016)
  • [6] ZHANG Tao, TANG Dunbing, ZHANG Zequn, Et al., Invasive 3D real-time supervision system for digital workshop, China Mechanical Engineering, 29, 8, pp. 990-999, (2018)
  • [7] YIN Chao, ZHANG Fei, LI Xiaobin, Et al., Visualization dynamic monitoring system of production execution for multi-variety and small-batch job shop, Computer Integrated Manufacturing Systems, 19, 1, pp. 46-54, (2013)
  • [8] ZHUANG Cunbo, LIU Jianhua, XIONG Hui, Et al., Assembly shop floor dynamic and real-time visual monitoring system for complex product, Computer Integrated Manufacturing Systems, 23, 6, pp. 1264-1276, (2017)
  • [9] HUANG Shaohua, GUO Yu, ZHA Shanshan, Et al., An Internet-of-Things-based production logistics optimisation method for discrete manufacturing, International Journal of Computer Integrated Manufacturing, 32, 1, pp. 13-26, (2019)
  • [10] TAO Fei, QI Qinglin, Make more digital twins, Nature, 573, pp. 490-491, (2019)
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