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Analysis of a closed-loop digital twin using discrete event simulation

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Abstract

Given recent advancements in technology and recognizing the evolution of smart manufacturing, the implementation of digital twins for factories and processes is becoming more common and more useful. Additionally, expansion in connectivity, growth in data storage, and the implementation of the industrial internet of things (IIoT) allow for greater opportunities not only with digital twins but with closed loop analytics. Discrete event simulation (DES) has been used to create digital twins and, in some instances, fitted with live connections to closely monitor factory operations. However, the benefits of a connected digital twin are not easily quantified. Therefore, a test bed demonstration factory was used, which implements smart technologies, to evaluate the effectiveness of a closed-loop digital twin in identifying and reacting to trends in production. This involves a digital twin of a factory process using DES. Although traditional DES is typically modeled using historical data, a DES system was developed which made use of live data to improve predictions. This model had live data updated directly to the DES model without user interaction, creating an adaptive and dynamic model. It was found that this DES with live data typically provided more accurate predictions of future performance and unforeseen near future problems when compared to the predictions of a traditional DES using only historic data, resulting in smarter decisions and implementation of more timely solutions.

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Availability of data and material

The datasets used and material of this study may be made available by the corresponding author upon reasonable request.

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Acknowledgements

The smart manufacturing lab at the BYU helped to develop this smart demonstration factory test bed. Software was provided by PTC and FlexSim. We acknowledge Tanner Poulton from the development team at FlexSim and Peter Zink with the academic team at PTC for the use of software and support.

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Authors and Affiliations

  1. Brigham Young University, Provo, UT, USA

    Andrew Eyring, Nathan Hoyt & Yuri Hovanski

  2. Northrop Grumman, Promontory, UT, USA

    Joe Tenny

  3. University of California Santa Cruz, Santa Cruz, CA, USA

    Reuben Domike

Authors
  1. Andrew Eyring
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  2. Nathan Hoyt
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  3. Joe Tenny
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  4. Reuben Domike
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  5. Yuri Hovanski
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Andrew Eyring, Nathan Hoyt, and Yuri Hovanski. Significant input and expertise were offered by Joe Tenny, Reuben Domike, and Yuri Hovanski. The first draft of the manuscript was written by Andrew Eyring, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Andrew Eyring.

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Eyring, A., Hoyt, N., Tenny, J. et al. Analysis of a closed-loop digital twin using discrete event simulation. Int J Adv Manuf Technol 123, 245–258 (2022). https://doi.org/10.1007/s00170-022-10176-5

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  • DOI: https://doi.org/10.1007/s00170-022-10176-5

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