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Research on Equipment Maintenance Guidance Technology Based on MR and Digital Twin

Published: 31 December 2021 Publication History

Abstract

Aiming at the problem that large-scale and complex equipment cannot be repaired without professional guidance, which caused by the complex structure, difficult maintenance operations, limited training conditions for maintenance personnel, a research technology for equipment maintenance guidance based on MR and digital twin technology is proposed. With the support of Mixed Reality (MR) technology and Digital Twin (DT) technology, the basic system framework of auxiliary maintenance based on the two is studied. This paper proposes a research technology for equipment maintenance guidance based on MR and DT technology. In the maintenance process, MR technology is used to solve the visualization problem, and the digital twin system could be used to solve the problem of resource allocation and work step arrangement.

References

[1]
Luo Q., et al. (2020)Multiple degradation mode analysis via gated recurrent unit mode recognizer and life predictors for complex equipment. J. Sci. Computers in Industry. 123: 47--53.
[2]
Xu Y. et al. (2019) Ontology-based Fault Diagnosis and Maintenance Process Generation of Electromechanical System. J. Sci. International Journal of Performability Engineering. 15:454--463.
[3]
Peng, Kern. (2021) Equipment Management in the Post-Maintenance Era: A New Alternative to Total Productive Maintenance (TPM). J. 16:46--66.
[4]
Khan D., Ullah S., Yan D.M., et al. (2018) Robust tracking through the design of high quality fiducial markers: an optimization tool for ARToolKit. J. IEEE Access. 22421--22433.
[5]
Fiala M. (2005) ARTag, a fiducial marker system using digital techniques. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). Seattle. pp: 32--40.
[6]
Grieves M., Vickers J. (2017) Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. J. Transdisciplinary Perspectives on Complex Systems. 12:67--75.
[7]
Tao F., Cheng J., Qi Q., et al. (2018) Digital twin-driven product design, manufacturing and service with big data. J. Sci. The International Journal of Advanced Manufacturing Technology. 2:18--31.

Cited By

View all
  • (2024)Comprehensive analysis of digital twins in smart cities: a 4200-paper bibliometric studyArtificial Intelligence Review10.1007/s10462-024-10781-857:6Online publication date: 27-May-2024
  • (2023)Operation and Maintenance Management Technology of Distribution Network Based on RFID Technology2023 World Conference on Communication & Computing (WCONF)10.1109/WCONF58270.2023.10235053(1-6)Online publication date: 14-Jul-2023
  • (2023)A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformationRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2022.10251581:COnline publication date: 1-Jun-2023

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  1. Research on Equipment Maintenance Guidance Technology Based on MR and Digital Twin

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    EITCE '21: Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering
    October 2021
    1723 pages
    ISBN:9781450384322
    DOI:10.1145/3501409
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 31 December 2021

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    Author Tags

    1. Equipment maintenance
    2. digital twin
    3. formatting
    4. maintenance guidance
    5. mixed reality
    6. resource allocation

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    EITCE 2021

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    EITCE '21 Paper Acceptance Rate 294 of 531 submissions, 55%;
    Overall Acceptance Rate 508 of 972 submissions, 52%

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    Cited By

    View all
    • (2024)Comprehensive analysis of digital twins in smart cities: a 4200-paper bibliometric studyArtificial Intelligence Review10.1007/s10462-024-10781-857:6Online publication date: 27-May-2024
    • (2023)Operation and Maintenance Management Technology of Distribution Network Based on RFID Technology2023 World Conference on Communication & Computing (WCONF)10.1109/WCONF58270.2023.10235053(1-6)Online publication date: 14-Jul-2023
    • (2023)A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformationRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2022.10251581:COnline publication date: 1-Jun-2023

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