Abstract
Digital twin has developed rapidly during the last two years, which provides a digital transformation from physical space to virtual space for real-time prediction, monitoring, control and optimization in industry. The visualization particle system based on mechanism model data can expand the digital twin to more fields since it is hard to directly observe the data in the production process, such as fluid, gas, and high-temperature raw materials. Although mechanism model is good at resolving the production data, the visualization mode is so simple so that users can only read the operation status in the form of numerical charts. In this paper, a visual particle system based on mechanism model data is achieved with Unity SRP for digital twin. The dedicated data conversion and visualization methods are proposed and an interactive editor is developed. Through a demo application in the iron and steel smelting scenario, mechanism model the system is proved to present a satisfactory visualization effect.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rosen, R., Von Wichert, G., Lo, G., et al.: About the importance of autonomy and digital twins for the future of manufacturing. IFAC PapersOnLine 48(3), 567–572 (2015)
Grieves, M.W.: Product lifecycle management: the new paradigm for enterprises. Int. J. Prod. Dev. 2(1), 1–8 (2005)
Wang, C., Ma, W., Luo, S.: Study on curve-passing performance of the electric flatcar. Mach. Des. Manuf. (8): 140–142 (2014)
Pittarello, F.: Experimenting with PlayVR, a virtual reality experience for the world of theater. In: The, Bi Conference, pp. 1–10 (2017)
Grieves, M.: Product lifecycle management: driving the next generation of lean thinking. J. Prod. Innov. Manag. 24(3), 278–280 (2011)
Lin, C.-H., Hsu, P.-H.: Integrating procedural modelling process and immersive VR environment for architectural design education. In: MATEC Web Conference (2017)
Litt, J.S., Simon, D.L., Meyer, C., et al.: NASA aviation safety program: aircraft engine health management data mining tools roadmap. In: Aerosense. International Society for Optics and Photonics (2000)
Internet of things of things-based cloud manufacturing service system. IEEE Trans. Ind. Inform. 10(2), 1435–1422 (2014)
Grieves, M.: Virtually Perfect: Driving Innovative and Lean Products through Product Lifecycle Management. Space Coast Press, Florida (2011)
Grieves, M.: Digital Twin: Manufacturing Excellence through Virtual Factory Replication. Florida Institute of Technology, vol. 4, pp. 1–7 (2015)
Tao, F., Zhang, M., Nee, A.: Digital Twin Driven Smart Manufacturing. Elsevier, Amsterdam (2019)
Wired Brand Lab. Digital twin: bridging the physical-digital divide [EB/OL]. https://www.ibm.com/blogs/internet-ofthings/iot-digital-twin-enablers/
Swedberg, C.: Digital twins bring value to big RFID and IoT data [EB/OL]. http://www.rfidjournal.com/articles/view?17421
Ghosh, A.K., Ullah, S., Kubo, A.: Hidden Markov model-based digital twin construction for futuristic manufacturing systems. Artif. Intell. Eng. Des. Anal. Manuf. 33(3), 317–331 (2019)
Tong, X., Liu, Q., Pi, S., et al.: Real-time machining data application and service based on IMT digital twin. J. Intell. Manuf. (2) (2019)
Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol (2020)
Acknowledgements
Supported by the Fundamental Research Funds for the Central Universities under Grant Number: N2017003 and N2017004.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Gu, Z., Gao, T. (2021). A Visual Particle System Based on Mechanism Model Data in Digital Twin. In: Barolli, L., Poniszewska-Maranda, A., Park, H. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing . IMIS 2020. Advances in Intelligent Systems and Computing, vol 1195. Springer, Cham. https://doi.org/10.1007/978-3-030-50399-4_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-50399-4_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-50398-7
Online ISBN: 978-3-030-50399-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)