Revisiting digital twins: Origins, fundamentals, and practices

Abstract

The digital twins (DT) has quickly become a hot topic since it was proposed. It appears in all kinds of commercial propaganda and is widely quoted by academic circles. However, the term DT has misstatements and is misused in business and academics. This study revisits DT and defines it to be a more advanced system/product/service modeling and simulation environment that combines most modern information communication technologies (ICTs) and engineering mechanism digitization and characterized by system/product/service life cycle management, physically geometric visualization, real-time sensing and measurement of system operating conditions, predictability of system performance/safety/lifespan, and complete engineering mechanisms-based simulations. The idea of DT originates from modeling and simulation practices of engineering informatization, including virtual manufacturing (VM), model predictive control, and building information modeling (BIM). On the basis of the two-element VM model, we propose a three-element model to represent DT. DT does not have its unique technical characteristics. The existing practices of DT are extensions of the engineering informatization embracing modern ICTs. These insights clarify the origin of DT and its technical essentials.

Graphical abstract

Keywords

virtual manufacturing / digital twins / modeling and simulation / digitization / computational engineering

References

[1] Deng, T Zhang, K Shen, Z J M (2021). A systematic review of a digital twin city: A new pattern of urban governance toward smart cities. Journal of Management Science and Engineering, 6( 2): 125–134

[2] García, C E Prett, D M Morari, M (1989). Model predictive control: Theory and practice — A survey. Automatica, 25( 3): 335–348

[3] Ghosh, A K Ullah, A S Teti, R Kubo, A (2021). Developing sensor signal-based digital twins for intelligent machine tools. Journal of Industrial Information Integration, 24: 100242

[4] GrievesM W (2005a). Product Lifecycle Management: Driving the Next Generation of Lean Thinking. New York: McGraw-Hill

[5] Grieves, M W (2005b). Product lifecycle management: The new paradigm for enterprises. International Journal of Product Development, 2( 1/2): 71–84

[6] GrievesM WVickersJ (2017). Digital Twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. In: Kahlen F J, Flumerfelt S, Alves A, eds. Transdisciplinary Perspectives on Complex Systems. Cham: Springer, 85–113

[7] Hernández, L A Hernández, S (1997). Application of digital 3D models on urban planning and highway design. WIT Transactions on the Built Environment, 33: 391–402

[8] Khajavi, S H Motlagh, N H Jaribion, A Werner, L C Holmström, J (2019). Digital Twin: Vision, benefits, boundaries, and creation for buildings. IEEE Access, 7: 147406–147419

[9] Kritzinger, W Karner, M Traar, G Henjes, J Sihn, W (2018). Digital twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine, 51( 11): 1016–1022

[10] Laiserin, J (2002). Comparing pommes and naranjas. The Laiserin Letter, 15

[11] Leng, J Wang, D Shen, W Li, X Y Liu, Q Chen, X (2021). Digital twins-based smart manufacturing system design in Industry 4.0: A review. Journal of Manufacturing Systems, 60: 119–137

[12] Liu, M N Fang, S L Dong, H Y Xu, C Z (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58( Part B): 346–361

[13] Miettinen, R Paavola, S (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43: 84–91

[14] Onosato, M Iwata, K (1993). Development of a virtual manufacturing system by integrating product models and factory models. CIRP Annals, 42( 1): 475–478

[15] Opoku, D G J Perera, S Osei-Kyei, R Rashidi, M (2021). Digital twin application in the construction industry: A literature review. Journal of Building Engineering, 40: 102726

[16] Pylianidis, C Osinga, S Athanasiadis, I N (2021). Introducing digital twins to agriculture. Computers and Electronics in Agriculture, 184: 105942

[17] Qin, S J Badgwell, T A (2003). A survey of industrial model predictive control technology. Control Engineering Practice, 11( 7): 733–764

[18] Richalet, J Rault, A Testud, J L Papon, J (1978). Model predictive heuristic control: Applications to industrial processes. Automatica, 14( 5): 413–428

[19] Semeraro, C Lezoche, M Panetto, H Dassisti, M (2021). Digital twin paradigm: A systematic literature review. Computers in Industry, 130: 103469

[20] ShaftoMConroyMDoyleRGlaessgenEKempCLeMoigneJWangL (2010). Modeling, simulation, information technology & processing roadmap. Technical Report. National Aeronautics and Space Administration

[21] Singh, S Weeber, M Birke, K P (2021). Advancing digital twin implementation: A toolbox for modelling and simulation. Procedia CIRP, 99: 567–572

[22] Tao, F Cheng, J F Qi, Q L Zhang, M Zhang, H Sui, F Y (2018). Digital twin-driven product design, manufacturing and service with big data. International Journal of Advanced Manufacturing Technology, 94( 9–12): 3563–3576

[23] Tao, F Zhang, H Liu, A Nee, A Y C (2019). Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 15( 4): 2405–2415

[24] TodorovicM HDattaRStevanovicLSheXCioffiPMandrusiakGRowdenBSzczesnyPDaiJFrangiehT (2016). Design and testing of a modular SiC based power block. In: Proceedings of International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management. Nuremberg: VDE, 1–4

[25] VanDerHorn, E Mahadevan, S (2021). Digital Twin: Generalization, characterization and implementation. Decision Support Systems, 145: 113524

[26] Volk, R Stengel, J Schultmann, F (2014). Building Information Modeling (BIM) for existing buildings: Literature review and future needs. Automation in Construction, 38: 109–127

[27] Wu, Y Wang, X J He, Y Huang, X W Xiao, L J Guo, L X (2021). Review on the technology and application of digital twin in manufacturing industry. Modern Manufacturing Engineering, ( 9): 137–145

[28] Zhang, L (2020). Cold thinking about digital twins and the modeling and simulation technologies. Journal of System Simulation, 32( 4): 1–10

[29] Zhang, L Zhou, L Horn, B K (2021). Building a right digital twin with model engineering. Journal of Manufacturing Systems, 59: 151–164

[30] Zhou, J H Wu, B Yang, S Z (2000). Overview of virtual manufacturing system. Bulletin of National Natural Science Foundation of China, 14( 5): 279–283, 27

RIGHTS & PERMISSIONS

Higher Education Press