政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143767
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113311/144292 (79%)
造访人次 : 50921341      在线人数 : 870
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/143767


    题名: 數位孿生之發展與應用:以製造業為例
    The Development and Application of Digital Twin: Taking Manufacturing Industry as an Example
    作者: 闕永杰
    Chueh, Yung-Chieh
    贡献者: 謝明華
    Hsieh, Ming-Hua
    闕永杰
    Chueh, Yung-Chieh
    关键词: 數位孿生
    智慧製造
    工業4.0
    虛實整合
    日期: 2023
    上传时间: 2023-03-09 18:21:55 (UTC+8)
    摘要: 本文採以文獻探討與分析,介紹數位孿生技術之歷史及其應用,進一步介
    紹五維數位孿生技術。在製造業應用方面,以製造業產品生命週期、航太業以 及汽車產業作為例子介紹其應用。接續介紹較為進階的數位孿生現場控制技 術,該技術由 Tao and Zhang (2017)首先提出,以優化製造業產品生產流程,以 實體數據與虛擬分身交互數據傳輸與作用,即時的優化生產線流程,達到最低 能耗以提升生產效率。
    參考文獻: Adam Mussomeli, D. G., and Stephen Laaper. (2016). The rise of the digital supply network. Retrieved from
    /content/www/globalblueprint/en/insights/focus/industry-4-0/digital-
    transformation-in-supply-chain.html
Allaire, D., Kordonowy, D., Lecerf, M., Mainini, L., & Willcox, K. (2014).
    Multifidelity DDDAS methods with application to a self-aware aerospace
    vehicle. Procedia Computer Science, 29, 1182-1192.
Boschert, S., & Rosen, R. (2016). Digital twin—the simulation aspect. In
    Mechatronic futures (pp. 59-74): Springer.
Bruynseels, K., Santoni de Sio, F., & Van den Hoven, J. (2018). Digital twins in
    health care: ethical implications of an emerging engineering paradigm.
    Frontiers in genetics, 31.
CeArley, D., Burke, B., Searle, S., & Walker, M. J. (2016). Top 10 strategic
    technology trends for 2018. The Top, 10, 1-246.
Cearley, D. W., Burke, B., & Walker, M. (2019). Top 10 strategic technology trends
    for.
. The cheap, convenient cloud,. (2015, 15 April 2015). Economist. Retrieved from
    https://www.economist.com/business/2015/04/18/the-cheap-convenient-cloud
    Choi, S., & Chan, A. (2004). A virtual prototyping system for rapid product development. Computer-aided design, 36(5), 401-412.
    Colombo, A. W., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., Harrison, R., . . . Lastra, J. L. (2014). Industrial cloud-based cyber-physical systems. The Imc-aesop Approach, 22, 4-5.
    Coronado, P. D. U., Lynn, R., Louhichi, W., Parto, M., Wescoat, E., & Kurfess, T. (2018). Part data integration in the Shop Floor Digital Twin: Mobile and cloud technologies to enable a manufacturing execution system. Journal of manufacturing systems, 48, 25-33.
    Croatti, A., Gabellini, M., Montagna, S., & Ricci, A. (2020). On the integration of agents and digital twins in healthcare. Journal of Medical Systems, 44(9), 1-8.
    Damiani, L., Demartini, M., Giribone, P., Maggiani, M., Revetria, R., & Tonelli, F. (2018). Simulation and digital twin based design of a production line: A case

    53
    study. Paper presented at the Proceedings of the International MultiConference
    of Engineers and Computer Scientists.
Glaessgen, E., & Stargel, D. (2012). The digital twin paradigm for future NASA and
    US Air Force vehicles. Paper presented at the 53rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference 20th AIAA/ASME/AHS adaptive structures conference 14th AIAA.
    Grieves, M. (2014). Digital twin: manufacturing excellence through virtual factory replication. White paper, 1(2014), 1-7.
    Grieves, M. W. (2005). Product lifecycle management: the new paradigm for enterprises. International Journal of Product Development, 2(1-2), 71-84.
    Hempel, V. (2017). Healthcare Solution Testing for Future| Digital Twins in Healthcare. Digital Health Network, 29.
    Leitao, P., Karnouskos, S., Ribeiro, L., Lee, J., Strasser, T., & Colombo, A. W. (2016). Smart agents in industrial cyber–physical systems. Proceedings of the IEEE, 104(5), 1086-1101.
    Leiva, C. (2016). Demystifying the digital thread and digital twin concepts. Industry Week, 1(2016), 2016.
    Liu, Q., Zhang, H., Leng, J., & Chen, X. (2019). Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system. International Journal of Production Research, 57(12), 3903-3919.
    Liu, Y. (2017). Lockheed martin space systems company makes use of digital twins speed F-35 fighter production. In.
    Liu, Z., Yang, D.-s., Wen, D., Zhang, W.-m., & Mao, W. (2011). Cyber-physical- social systems for command and control. IEEE Intelligent Systems, 26(4), 92- 96.
    Magargle, R., Johnson, L., Mandloi, P., Davoudabadi, P., Kesarkar, O., Krishnaswamy, S., . . . Pitchaikani, A. (2017). A simulation-based digital twin for model-driven health monitoring and predictive maintenance of an automotive braking system. Paper presented at the Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017.
    Monostori, L. (2014). Cyber-physical production systems: Roots, expectations and R&D challenges. Procedia Cirp, 17, 9-13.
    54
    Murray, L. (2017). Lockheed Martin forecasts tech trends for defense in 2018. Retrieved from https://dallasinnovates.com/lockheed-martin-forecasts-tech- trends-for-defense-in-2018/
    Reifsnider, K., & Majumdar, P. (2013). Multiphysics stimulated simulation digital twin methods for fleet management. Paper presented at the 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference.
    Research, G. V. (2022). Digital Twin Market Size & Share Report, 2022-2030. Retrieved from
    Shafto, M., Conroy, M., Doyle, R., Gleassgen, E., Kemp, C., LeMoigne, J., & Wang, L. (2010). Draft modelling, simulation, information technology &processing roadmap. Technology Area, 11.
    Stark, J. (2020). Product lifecycle management (PLM). In Product lifecycle management (Volume 1) (pp. 1-33): Springer.
    Stark, R., Kind, S., & Neumeyer, S. (2017). Innovations in digital modelling for next generation manufacturing system design. Cirp Annals, 66(1), 169-172.
    Swedberg, C. (2018). Digital twins bring value to big RFID and IoT data. RFID J. Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018). Digital twin-driven
    product design, manufacturing and service with big data. The International
    Journal of Advanced Manufacturing Technology, 94(9), 3563-3576.
Tao, F., Cheng, Y., Cheng, J., Zhang, M., Xu, W., & Qi, Q. (2017). Theories and
    technologies for cyber-physical fusion in digital twin shop-floor.
Tao, F., Liu, W., Liu, J., Liu, X., Liu, Q., Qu, T., . . . Xu, W. (2018). Digital twin and
    its potential application exploration. Computer Integrated Manufacturing
    Systems, 24(1), 1-18.
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., . . . Nee, A. Y. (2019). Digital
    twin-driven product design framework. International Journal of Production
    Research, 57(12), 3935-3953.
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. (2018a). Digital twin in industry: State-of-
    the-art. IEEE Transactions on industrial informatics, 15(4), 2405-2415. Tao, F., & Zhang, M. (2017). Digital twin shop-floor: a new shop-floor paradigm
    towards smart manufacturing. IEEE access, 5, 20418-20427.
Tao, F., Zhang, M., Cheng, J., & Qi, Q. (2017). Digital twin workshop: a new
    paradigm for future workshop. Computer Integrated Manufacturing Systems, 23(1), 1-9.



    55
    Tao, F., Zhang, M., Liu, Y., & Nee, A. Y. (2018b). Digital twin driven prognostics and health management for complex equipment. Cirp Annals, 67(1), 169-172.
    Tao, F., Zhang, M., & Nee, A. Y. C. (2019). Digital twin driven smart manufacturing: Academic Press.
    Tuegel, E. (2012). The airframe digital twin: some challenges to realization. Paper presented at the 53rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference 20th AIAA/ASME/AHS adaptive structures conference 14th AIAA.
    Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011). Reengineering aircraft structural life prediction using a digital twin. International Journal of Aerospace Engineering, 2011.
    Wanasinghe, T. R., Wroblewski, L., Petersen, B. K., Gosine, R. G., James, L. A., De Silva, O., . . . Warrian, P. J. (2020). Digital twin for the oil and gas industry: Overview, research trends, opportunities, and challenges. IEEE access, 8, 104175-104197.
    描述: 碩士
    國立政治大學
    經營管理碩士學程(EMBA)
    110932101
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0110932101
    数据类型: thesis
    显示于类别:[經營管理碩士學程EMBA] 學位論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    210101.pdf1371KbAdobe PDF239检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈