Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The concept of Industry 4.0 has now become a fact. One of its key technological solutions – the digital twin – serves as a bridge between the real and virtual worlds. Designs for both products and tools to make these products are generated in the virtual world. Thanks to the simulation capabilities of these digital replicas, it is possible to eliminate design flaws well before the creation of physical prototypes. Thus, the question naturally arises as to what degree these mathematical models of objects, processes or services replicate their physical counterparts. A correctly generated digital twin is not only a model or visualisation of its counterpart; it also reflects its dynamic behaviour. The issue of digital twins is a very broad one, and currently on the market, there are appearing an increasing number of tools available for the development of these twins. More and more often, 3D modelling software can be integrated with a control system model, facilitating the testing of newly designed objects in the virtual world. This paper presents the concept of building simplified digital twins in a web application environment. In addition to educational usage, the presented idea should find application in the design of small production lines, significantly affecting the cost of producing a digital twin.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
110--119
Opis fizyczny
Bibliogr. 26 poz., fig.
Twórcy
autor
- Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, ul. Mickiewicza 30, 30-059 Krakow, Poland
autor
- Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, ul. Mickiewicza 30, 30-059 Krakow, Poland
Bibliografia
- 1. Qin H., Wang H., Zhang Y., Lin L. Constructing Digital Twin for Smart Manufacturing, IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD). 2021; 638–642.
- 2. Wagg, D.J., Worden, K., Barthorpe, R.J., Gardner, P. Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications. ASME. ASME J. Risk Uncertainty Part B. 2020; 6(3): 030901.
- 3. Kutin A.A., Bushuev, V.V., Molodtsov V.V. Digital twins of mechatronic machine tools for modern manufacturing. IOP Conference Series: Materials Science and Engineering. 2019; 568(1): 012070.
- 4. Cheng K., Wang Q., Yang D., Dai Q., Wang M. Digital-Twins-Driven Semi-Physical Simulation for Testing and Evaluation of Industrial Software in a Smart Manufacturing System. Machines. 2022; 10(5): 388.
- 5. Figueiras P., Lourenço L., Costa R., Graça D., Garcia G., Jardim-Gonçalves R. Big Data Provision for Digital Twins in Industry 4.0 Logistics Processes, 2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). 2021; 516–521.
- 6. Maulshree S., Srivastava R., Fuenmayor E., Kuts V., Qiao J., Murray N., Devine D. Applications of Digital Twin across Industries: A Review, Applied Sciences. 2022; 12(11): 5727.
- 7. Lalik K., Flaga S. A real-time distance measurement system for a digital twin using mixed reality goggles. Sensors. 2021; 21(23): 7870.
- 8. Oborski P., Wysocki P. Intelligent Visual Quality Control System Based on Convolutional Neural Networks for Holonic Shop Floor Control of Industry 4.0 Manufacturing Systems. Advances in Science and Technology Research Journal. 2022; 16(2): 89–98.
- 9. Gaska P., Harmatys W., Gruza M., Gaska A., Sladek J. Simple Optical Coordinate Measuring System, Based on Fiducial Markers Detection, and its Accuracy Assessment. Advances in Science and Technology Research Journal. 2020; 14(4): 213–219.
- 10. Kuts V., Sarkans M., Otto T. Tähemaa T., Bondarenko Y. Digital Twin: Concept of Hybrid Programming for Industrial Robots – Use Case. Proceedings of the ASME 2019 International Mechanical Engineering Congress and Exposition. Volume 2B: Advanced Manufacturing. Salt Lake City, Utah, USA 2019.
- 11. Pizon, J., Gola, A., Swic, A. The Role and Meaning of the Digital Twin Technology in the Process of Implementing Intelligent Collaborative Robots. In: Gapinski, B., Ciszak, O., Ivanov, V. (eds) Advances in Manufacturing III. MANUFACTURING 2022, Springer, 2022.
- 12. Staczek P., Pizon J., Danilczuk W., Gola A. A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR’s) Operating Environment – A Case Study, Sensors. 2021; 21(23): 7830.
- 13. Georgakopoulos D., Bamunuarachchi D. Digital Twins-based Application Development for Digital Manufacturing, 2021 IEEE 7th International Conference on Collaboration and Internet Computing (CIC). 2021, 87–95.
- 14. Yasin, A., Pang, T.Y., Cheng, C.T., Miletic, M. A Roadmap to Integrate Digital Twins for Small and Medium-Sized Enterprises. Appl. Sci. 2021; 11: 9479.
- 15. Herbus K., Ociepka P., Gwiazda A. Virtual activating of a robotised production cell with use of the mechatronics concept designer module of the PLM Siemens NX system. In International Conference on Intelligent Systems in Production Engineering and Maintenancel, Springer, Cham. 2018; 417–425.
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- 21. Lalik K., Kozek M., Dominik I., Łukasiewicz P. Adaptive MRAC Controller in the Effector Trajectory Generator for Industry 4.0 Machines, Advanced, Contemporary Control, Advances in Intelligent Systems and Computing, Springer, 2020.
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- 23. Evans E., Evans E.J. Domain-driven design: tackling complexity in the heart of software. AddisonWesley Professional, 2004.
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-509f6aed-d693-479d-9e35-4217fd6b41f3