Development of a Virtual Reality Model Using Digital Twin for Real-Time Data Analysis

被引:0
|
作者
Sahoo S.K. [1 ]
Nalinipriya G. [2 ]
Srinivasan P.S. [3 ]
Ramesh J.V.N. [4 ]
Ramamoorthy K. [5 ]
Soleti N. [6 ]
机构
[1] Department of EIE, CVR College of Engineering, Telangana, Hyderabad
[2] Department of IT, Saveetha Engineering College, Tamil Nadu, Chennai
[3] Department of Mathematics, Panimalar Engineering College, Tamil Nadu, Chennai
[4] Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P., Guntur
[5] Department of ECE, PSNA College of Engineering and Technology, Dindigul
[6] Computer Science, and Information Technology, MLR Institute of Technology, Hyderabad
关键词
Augmented reality; Digital twin; Implementation; Machining technology; Monitoring;
D O I
10.1007/s42979-023-01928-5
中图分类号
学科分类号
摘要
Digital Twin (DT) machining technology enables real-time monitoring of machining operations, ensuring precision in the process. The virtual–real separation display method utilizes advanced DT systems, but it hinders the effective transmission of essential data to local technicians, thereby limiting the utilization of field processing supported by DT systems. Augmented Reality (AR) is employed to address the issue of monitoring the machining process, which is facilitated by a DT system. First, a dynamic multi-view for AR is created by incorporating data from various sources. Second, ongoing observation of the intermediate processing in AR promotes collaboration between the DT machining system and operators, particularly for complex products, preventing irreparable errors when the final product is nearly complete. The framework includes a module for data representation and detailed explanations are provided for the modules focused on data management and data organization. In a case study, the application of cutting tool wear prediction demonstrates the feasibility and the effectiveness of the proposed method for data construction. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
引用
收藏
相关论文
共 50 条
  • [31] Real-time machining data application and service based on IMT digital twin
    Tong, Xin
    Liu, Qiang
    Pi, Shiwei
    Xiao, Yao
    JOURNAL OF INTELLIGENT MANUFACTURING, 2020, 31 (05) : 1113 - 1132
  • [32] REAL-TIME DIGITAL ANALYSIS SYSTEM FOR BIOLOGICAL DATA
    MUNDIE, JR
    OESTREICHER, HL
    VONGIERK.HE
    IEEE SPECTRUM, 1966, 3 (10) : 116 - +
  • [33] Evaluating Voltage Estimation in a Nanogrid Using Digital Twin Models and Real-Time Smart Meter Data
    Lopez-Lorente, Javier
    Xydas, Charalambos M.
    Makrides, George
    Georghiou, George E.
    2022 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES, SEST, 2022,
  • [34] Real-time event-based platform for the development of digital twin applications
    Carlos Eduardo Belman López
    The International Journal of Advanced Manufacturing Technology, 2021, 116 : 835 - 845
  • [35] Development of a Real-Time Track Solver for Digital Twin of the Underwater Tracked Vehicle
    Cho, Han-Seung
    Sohn, Jeong-Hyun
    Han, Jong-Boo
    Yeu, Tae-Kyeong
    INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY, 2025,
  • [36] Real-time event-based platform for the development of digital twin applications
    Lopez, Carlos Eduardo Belman
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 116 (3-4): : 835 - 845
  • [37] Virtual reality myringotomy simulation with real-time deformation: Development and validity testing
    Ho, Andrew K.
    Alsaffar, Hussain
    Doyle, Philip C.
    Ladak, Hanif M.
    Agrawal, Sumit K.
    LARYNGOSCOPE, 2012, 122 (08): : 1844 - 1851
  • [38] A REAL-TIME MECHANICAL STRUCTURES MONITORING SYSTEM BASED ON DIGITAL TWIN, IOT AND AUGMENTED REALITY
    Revetria, Roberto
    Tonelli, Flavio
    Damiani, Lorenzo
    Demartini, Melissa
    Bisio, Federico
    Peruzzo, Nicola
    2019 SPRING SIMULATION CONFERENCE (SPRINGSIM), 2019,
  • [39] Digital Twin Model: A Real-Time Emotion Recognition System for Personalized Healthcare
    Subramanian, Barathi
    Kim, Jeonghong
    Maray, Mohammed
    Paul, Anand
    IEEE ACCESS, 2022, 10 : 81155 - 81165
  • [40] REALITY CHECK: IMPROVING REAL-TIME PIPELINE MONITORING USING NEAR REAL-TIME FLUID DATA
    Jutras, Joseph
    Barlow, Rick
    IPC2008: PROCEEDINGS OF THE ASME INTERNATIONAL PIPELINE CONFERENCE - 2008, VOL 1, 2009, : 641 - 649