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Tiismus, H., Kallaste, A., Belahcen, A., Rassolkin, A., Vaimann, T., & Shams Ghahfarokhi, P. (2021). Additive manufacturing and performance of E-type transformer core. Energies, 14(11), 3278.TiismusH.KallasteA.BelahcenA.RassolkinA.VaimannT.Shams GhahfarokhiP. (2021). Additive manufacturing and performance of E-type transformer core. Energies, 14(11), 3278.Search in Google Scholar
Yang, Z., Shang, W. L., Zhang, H., Garg, H., & Han, C. (2022). Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework. Applied Energy, 311, 118687.YangZ.ShangW. L.ZhangH.GargH.HanC. (2022). Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework. Applied Energy, 311, 118687.Search in Google Scholar
Plotkowski, A., Carver, K., List, F., Pries, J., Li, Z., Rossy, A. M., & Leonard, D. (2020). Design and performance of an additively manufactured high-Si transformer core. Materials & Design, 194, 108894.PlotkowskiA.CarverK.ListF.PriesJ.LiZ.RossyA. M.LeonardD. (2020). Design and performance of an additively manufactured high-Si transformer core. Materials & Design, 194, 108894.Search in Google Scholar
Cudok, F., Giannetti, N., Ciganda, J. L. C., Aoyama, J., Babu, P., Coronas, A., … & Ziegler, F. (2021). Absorption heat transformer-state-of-the-art of industrial applications. Renewable and Sustainable Energy Reviews, 141, 110757.CudokF.GiannettiN.CigandaJ. L. C.AoyamaJ.BabuP.CoronasA.ZieglerF. (2021). Absorption heat transformer-state-of-the-art of industrial applications. Renewable and Sustainable Energy Reviews, 141, 110757.Search in Google Scholar
Li, L., Qu, T., Liu, Y., Zhong, R. Y., Xu, G., Sun, H., … & Ma, C. (2020). Sustainability assessment of intelligent manufacturing supported by digital twin. IEEE Access, 8, 174988-175008.LiL.QuT.LiuY.ZhongR. Y.XuG.SunH.MaC. (2020). Sustainability assessment of intelligent manufacturing supported by digital twin. IEEE Access, 8, 174988-175008.Search in Google Scholar
Liu, H., Liu, Z., Jia, W., Lin, X., & Zhang, S. (2020). A novel transformer-based neural network model for tool wear estimation. Measurement Science and Technology, 31(6), 065106.LiuH.LiuZ.JiaW.LinX.ZhangS. (2020). A novel transformer-based neural network model for tool wear estimation. Measurement Science and Technology, 31(6), 065106.Search in Google Scholar
Magisetty, R., & Cheekuramelli, N. S. (2019). Additive manufacturing technology empowered complex electromechanical energy conversion devices and transformers. Applied Materials Today, 14, 35-50.MagisettyR.CheekuramelliN. S. (2019). Additive manufacturing technology empowered complex electromechanical energy conversion devices and transformers. Applied Materials Today, 14, 35-50.Search in Google Scholar
Hellmann, S., Abplanalp, M., Hofstetter, L., & Noe, M. (2017). Manufacturing of a 1-MVA-class superconducting fault current limiting transformer with recovery-under-load capabilities. IEEE Transactions on Applied Superconductivity, 27(4), 1-5.HellmannS.AbplanalpM.HofstetterL.NoeM. (2017). Manufacturing of a 1-MVA-class superconducting fault current limiting transformer with recovery-under-load capabilities. IEEE Transactions on Applied Superconductivity, 27(4), 1-5.Search in Google Scholar
Orosz, T. (2019). Evolution and modern approaches of the power transformer cost optimization methods. Periodica Polytechnica Electrical Engineering and Computer Science, 63(1), 37-50.OroszT. (2019). Evolution and modern approaches of the power transformer cost optimization methods. Periodica Polytechnica Electrical Engineering and Computer Science, 63(1), 37-50.Search in Google Scholar
Fritsch, M., & Wolter, M. (2022). High-frequency current transformer design and construction guide. IEEE Transactions on Instrumentation and Measurement, 71, 1-9.FritschM.WolterM. (2022). High-frequency current transformer design and construction guide. IEEE Transactions on Instrumentation and Measurement, 71, 1-9.Search in Google Scholar
Yin, S., Zhang, N., Ullah, K., & Gao, S. (2022). Enhancing digital innovation for the sustainable transformation of manufacturing industry: a pressure-state-response system framework to perceptions of digital green innovation and its performance for green and intelligent manufacturing. Systems, 10(3), 72.YinS.ZhangN.UllahK.GaoS. (2022). Enhancing digital innovation for the sustainable transformation of manufacturing industry: a pressure-state-response system framework to perceptions of digital green innovation and its performance for green and intelligent manufacturing. Systems, 10(3), 72.Search in Google Scholar
An, K., & Zhang, Y. (2022). LPViT: a transformer based model for PCB image classification and defect detection. IEEE Access, 10, 42542-42553.AnK.ZhangY. (2022). LPViT: a transformer based model for PCB image classification and defect detection. IEEE Access, 10, 42542-42553.Search in Google Scholar
Hung, M. H., Lin, Y. C., Hsiao, H. C., Chen, C. C., Lai, K. C., Hsieh, Y. M., … & Cheng, F. T. (2022). A novel implementation framework of digital twins for intelligent manufacturing based on container technology and cloud manufacturing services. IEEE Transactions on Automation Science and Engineering, 19(3), 1614-1630.HungM. H.LinY. C.HsiaoH. C.ChenC. C.LaiK. C.HsiehY. M.ChengF. T. (2022). A novel implementation framework of digital twins for intelligent manufacturing based on container technology and cloud manufacturing services. IEEE Transactions on Automation Science and Engineering, 19(3), 1614-1630.Search in Google Scholar
Tenbohlen, S., Jagers, J., & Vahidi, F. (2017, September). Standardized survey of transformer reliability: On behalf of CIGRE WG A2. 37. In 2017 International Symposium on Electrical Insulating Materials (ISEIM) (Vol. 2, pp. 593-596). IEEE.TenbohlenS.JagersJ.VahidiF. (2017, September). Standardized survey of transformer reliability: On behalf of CIGRE WG A2. 37. In 2017 International Symposium on Electrical Insulating Materials (ISEIM) (Vol. 2, pp. 593-596). IEEE.Search in Google Scholar
He, B., & Bai, K. J. (2021). Digital twin-based sustainable intelligent manufacturing: a review. Advances in Manufacturing, 9(1), 1-21.HeB.BaiK. J. (2021). Digital twin-based sustainable intelligent manufacturing: a review. Advances in Manufacturing, 9(1), 1-21.Search in Google Scholar
Zhou, G., Zhang, C., Li, Z., Ding, K., & Wang, C. (2020). Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. International Journal of Production Research, 58(4), 1034-1051.ZhouG.ZhangC.LiZ.DingK.WangC. (2020). Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. International Journal of Production Research, 58(4), 1034-1051.Search in Google Scholar
Wang, B., Tao, F., Fang, X., Liu, C., Liu, Y., & Freiheit, T. (2021). Smart manufacturing and intelligent manufacturing: A comparative review. Engineering, 7(6), 738-757.WangB.TaoF.FangX.LiuC.LiuY.FreiheitT. (2021). Smart manufacturing and intelligent manufacturing: A comparative review. Engineering, 7(6), 738-757.Search in Google Scholar
Liu Xiaojun,Wang Chongxin,Huang Jiasheng,Ni Zhonghua,Salam Musharaf,Yan Yuehui & Feng Jindan. (2024). Fusion method for digital twin model of a production line. The International Journal of Advanced Manufacturing Technology(11-12),6145-6167.LiuXiaojunWangChongxinHuangJiashengNiZhonghuaSalamMusharafYanYuehuiFengJindan (2024). Fusion method for digital twin model of a production line. The International Journal of Advanced Manufacturing Technology(11-12),6145-6167.Search in Google Scholar
Roberto Rosario Corsini,Antonio Costa,Sergio Fichera & Jose M. Framinan. (2024). Digital twin model with machine learning and optimization for resilient production–distribution systems under disruptions. Computers & Industrial Engineering110145-.Roberto RosarioCorsiniAntonioCostaSergioFicheraJose M.Framinan (2024). Digital twin model with machine learning and optimization for resilient production–distribution systems under disruptions. Computers & Industrial Engineering110145-.Search in Google Scholar
Jinfeng Liu,Qiukai Ji,Xiaohu Zhang,Yu Chen,Yiming Zhang,Xiaojun Liu & Mingming Tang. (2023). Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line. Journal of Intelligent Manufacturing(7),3353-3375.JinfengLiuQiukaiJiXiaohuZhangYuChenYimingZhangXiaojunLiuMingmingTang (2023). Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line. Journal of Intelligent Manufacturing(7),3353-3375.Search in Google Scholar