IDEAS home Printed from https://ideas.repec.org/a/baq/jetart/v4y2023i13p66-78.html
   My bibliography  Save this article

Identification of influence of digital twin technologies on production systems: a return on investment-based approach

Author

Listed:
  • Kristof Banyai

    (University of Miskolc)

  • Laszlo Kovacs

    (University of Miskolc)

Abstract

The object of this study is the impact of different digital twin solutions on the performance of job-shop manufacturing systems, while economic aspects are also taken into consideration. This paper proposes an approach to analyze the impact of different identification systems on the efficiency and ROI of digital twin deployment in production systems. In order to achieve this aim, let’s analyze the investment and operation cost of different Internet of Things technologies. The next phase of the research work was the definition of performance parameters, which makes it possible to analyze the impact of different digital twin solutions on the productivity of the job-shop manufacturing system. It is possible to choose four financial indicators to analyze the economic impact of digital twin solution on job-shop manufacturing: return on investment, compound annual growth rate, internal rate of return and net present value. Our approach is based on a novel agent-based simulation model using AnyLogic simulation tool. From the results of this productivity analyses, the model computes the financial indicators, which describe the expected financial impact of the investment and operation cost. It is compared the impact of barcodes and radiofrequency identification technologies on the financial and technological impact of the job-shop manufacturing environment. The numerical analysis of a job-shop manufacturing system shows, that the radiofrequency identification-based digital twin solution has 9.2 % higher return on investment, 53 % higher net present value and 1.6 % higher compound annual growth rate. The model can be easily converted to analyze other types of manufacturing systems, which can lead to increased efficiency of digital twin solutions

Suggested Citation

  • Kristof Banyai & Laszlo Kovacs, 2023. "Identification of influence of digital twin technologies on production systems: a return on investment-based approach," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 4(13 (124)), pages 66-78, August.
    • Handle: RePEc:baq:jetart:v:4:y:2023:i:13:p:66-78
    DOI: 10.15587/1729-4061.2023.283876
    as

    Download full text from publisher

    File URL: https://journals.uran.ua/eejet/article/download/283876/278733
    Download Restriction: no
    File URL: https://libkey.io/10.15587/1729-4061.2023.283876?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sanguk Park & Sanghoon Lee & Sangmin Park & Sehyun Park, 2019. "AI-Based Physical and Virtual Platform with 5-Layered Architecture for Sustainable Smart Energy City Development," Sustainability, MDPI, vol. 11(16), pages 1-30, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Hakpyeong & Choi, Heeju & Kang, Hyuna & An, Jongbaek & Yeom, Seungkeun & Hong, Taehoon, 2021. "A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    2. Li Zhao & Zhi-ying Tang & Xin Zou, 2019. "Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis," Sustainability, MDPI, vol. 11(23), pages 1-28, November.
    3. Rong Xie & Muyan Chen & Weihuang Liu & Hongfei Jian & Yanjun Shi, 2021. "Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
    4. Mateusz Tomal, 2020. "Moving towards a Smarter Housing Market: The Example of Poland," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    5. Ehab Shahat & Chang T. Hyun & Chunho Yeom, 2021. "City Digital Twin Potentials: A Review and Research Agenda," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    6. Qi Zhang & Hongyang Li & Xin Wan & Martin Skitmore & Hailin Sun, 2020. "An Intelligent Waste Removal System for Smarter Communities," Sustainability, MDPI, vol. 12(17), pages 1-27, August.
    7. Rasa Apanaviciene & Andrius Vanagas & Paris A. Fokaides, 2020. "Smart Building Integration into a Smart City (SBISC): Development of a New Evaluation Framework," Energies, MDPI, vol. 13(9), pages 1-19, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:baq:jetart:v:4:y:2023:i:13:p:66-78. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Iryna Prudius (email available below). General contact details of provider: https://journals.uran.ua/eejet/issue/archive .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.