Real-time machining data application and service based on IMT digital twin
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DOI: 10.1007/s10845-019-01500-0
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References listed on IDEAS
- Changqing Liu & Yingguang Li & Guanyan Zhou & Weiming Shen, 2018. "A sensor fusion and support vector machine based approach for recognition of complex machining conditions," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1739-1752, December.
- Sanjay Jain & Guodong Shao & Seung-Jun Shin, 2017. "Manufacturing data analytics using a virtual factory representation," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5450-5464, September.
- Tangbin Xia & Lifeng Xi, 2019. "Manufacturing paradigm-oriented PHM methodologies for cyber-physical systems," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1659-1672, April.
- Wei Ji & Shubin Yin & Lihui Wang, 2019. "A big data analytics based machining optimisation approach," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1483-1495, March.
- Fei Tao & Fangyuan Sui & Ang Liu & Qinglin Qi & Meng Zhang & Boyang Song & Zirong Guo & Stephen C.-Y. Lu & A. Y. C. Nee, 2019. "Digital twin-driven product design framework," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3935-3953, June.
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Cited by:
- Marco Bettiol & Mauro Capestro & Eleonora Di Maria & Roberto Ganau, 2024. "Is this time different? How Industry 4.0 affects firms’ labor productivity," Small Business Economics, Springer, vol. 62(4), pages 1449-1467, April.
- PengYu Wang & Wen-An Yang & YouPeng You, 2023. "A cyber-physical prototype system in augmented reality using RGB-D camera for CNC machining simulation," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3637-3658, December.
- Zengya Zhao & Sibao Wang & Zehua Wang & Shilong Wang & Chi Ma & Bo Yang, 2022. "Surface roughness stabilization method based on digital twin-driven machining parameters self-adaption adjustment: a case study in five-axis machining," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 943-952, April.
- Khairul Jauhari & Achmad Zaki Rahman & Mahfudz Huda & Achmad Widodo & Toni Prahasto, 2024. "Building digital-twin virtual machining for milling chatter detection based on VMD, synchro-squeeze wavelet, and pre-trained network CNNs with vibration signals," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3083-3114, October.
- Ahmed Ktari & Mohamed El Mansori, 2022. "Digital twin of functional gating system in 3D printed molds for sand casting using a neural network," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 897-909, March.
- Chi Ma & Hongquan Gui & Jialan Liu, 2023. "Self learning-empowered thermal error control method of precision machine tools based on digital twin," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 695-717, February.
- Aniket Nagargoje & Pavan Kumar Kankar & Prashant Kumar Jain & Puneet Tandon, 2023. "Application of artificial intelligence techniques in incremental forming: a state-of-the-art review," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 985-1002, March.
- Georgios Falekas & Athanasios Karlis, 2021. "Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects," Energies, MDPI, vol. 14(18), pages 1-26, September.
- Ayman AboElHassan & Soumaya Yacout, 2023. "A digital shadow framework using distributed system concepts," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3579-3598, December.
- Bettiol, Marco & Capestro, Mauro & Di Maria, Eleonora & Ganau, Roberto, 2024. "Is this time different?: how Industry 4.0 affects firms' labor productivity," LSE Research Online Documents on Economics 124545, London School of Economics and Political Science, LSE Library.
- Benjamin Lutz & Dominik Kisskalt & Andreas Mayr & Daniel Regulin & Matteo Pantano & Jörg Franke, 2021. "In-situ identification of material batches using machine learning for machining operations," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1485-1495, June.
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Keywords
Digital twin; Intelligent machine tool; Machining data; Data fusion; Data service;All these keywords.
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