A review of the roles of Digital Twin in CPS-based production systems

被引:841
作者
Negri, Elisa [1 ]
Fumagalli, Luca [1 ]
Macchi, Marco [1 ]
机构
[1] Politecn Milan, Dept Management Econ & Ind Engn, Pza Leonardo da Vinci 32, I-20133 Milan, Italy
来源
27TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING, FAIM2017 | 2017年 / 11卷
基金
欧盟地平线“2020”;
关键词
Digital Twin; Cyber-Physical Systems; Industry; 4.0; Production Systems; ONTOLOGIES; DESIGN;
D O I
10.1016/j.promfg.2017.07.198
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Digital Twin (DT) is one of the main concepts associated to the Industry 4.0 wave. This term is more and more used in industry and research initiatives; however, the scientific literature does not provide a unique definition of this concept. The paper aims at analyzing the definitions of the DT concept in scientific literature, retracing it from the initial conceptualization in the aerospace field, to the most recent interpretations in the manufacturing domain and more specifically in Industry 4.0 and smart manufacturing research. DT provides virtual representations of systems along their lifecycle. Optimizations and decisions making would then rely on the same data that are updated in real-time with the physical system, through synchronization enabled by sensors. The paper also proposes the definition of DT for Industry 4.0 manufacturing, elaborated by the European H2020 project MAYA, as a contribution to the research discussion about DT concept. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:939 / 948
页数:10
相关论文
共 51 条
  • [1] Semantic data management for the development and continuous reconfiguration of smart products and systems
    Abramovici, Michael
    Goebel, Jens Christian
    Dang, Hoang Bao
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2016, 65 (01) : 185 - 188
  • [2] [Anonymous], 2011, The impact of control technology
  • [3] [Anonymous], 2016, P 11 IEEE ACM IFIP I
  • [4] Arisoy E.B., 2017, ASME 2016 INT DES EN, DOI 10.1115/DETC2016
  • [5] Ashton K., 2009, RFID J, V22, P97, DOI DOI 10.1016/J.AMJCARD.2013.11.014
  • [6] Bajaj M., 2016, P AIAA SPACE, P1
  • [7] Isogeometric Fatigue Damage Prediction in Large-Scale Composite Structures Driven by Dynamic Sensor Data
    Bazilevs, Y.
    Deng, X.
    Korobenko, A.
    di Scalea, F. Lanza
    Todd, M. D.
    Taylor, S. G.
    [J]. JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME, 2015, 82 (09):
  • [8] Bielefeldt B, 2016, PROC ASME CONF SMART
  • [9] An ontological approach for reliable data integration in the industrial domain
    Borgo, Stefano
    [J]. COMPUTERS IN INDUSTRY, 2014, 65 (09) : 1242 - 1252
  • [10] Brettel M., 2014, International Journal of Science, Engineering and Technology, V8