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題名 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
貢獻者 謝明華
Hsieh, Ming-Hua
闕永杰
Chueh, Yung-Chieh
關鍵詞 數位孿生
智慧製造
工業4.0
虛實整合
日期 2023
上傳時間 9-Mar-2023 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
資料類型 thesis
dc.contributor.advisor 謝明華zh_TW
dc.contributor.advisor Hsieh, Ming-Huaen_US
dc.contributor.author (Authors) 闕永杰zh_TW
dc.contributor.author (Authors) Chueh, Yung-Chiehen_US
dc.creator (作者) 闕永杰zh_TW
dc.creator (作者) Chueh, Yung-Chiehen_US
dc.date (日期) 2023en_US
dc.date.accessioned 9-Mar-2023 18:21:55 (UTC+8)-
dc.date.available 9-Mar-2023 18:21:55 (UTC+8)-
dc.date.issued (上傳時間) 9-Mar-2023 18:21:55 (UTC+8)-
dc.identifier (Other Identifiers) G0110932101en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/143767-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經營管理碩士學程(EMBA)zh_TW
dc.description (描述) 110932101zh_TW
dc.description.abstract (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。		zh_TW
dc.description.tableofcontents 第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究方法與目的 9
第二章 數位孿生技術 10
第一節 數位孿生之發展 10
第二節 數位孿生之概念 16
第三節 五維度數位孿生 32
第三章 數位孿生技術之應用 38
第一節 產品生命週期數位孿生應用 39
第二節 製造業產業數位孿生應用 44
第三節 數位孿生現場控制技術 48
第四章 結論 51
參考文獻 53

圖次
圖 1 數位攣生市場預測 3
圖 2 全球數位孿生市場份額 – 產業 6
圖 3 數位孿生發展 13
圖 4 數位線程 28
圖 5 五維數位孿生技術 38
圖 6 產品生命週期管理 39		zh_TW
dc.format.extent 1404408 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110932101en_US
dc.subject (關鍵詞) 數位孿生zh_TW
dc.subject (關鍵詞) 智慧製造zh_TW
dc.subject (關鍵詞) 工業4.0zh_TW
dc.subject (關鍵詞) 虛實整合zh_TW
dc.title (題名) 數位孿生之發展與應用：以製造業為例zh_TW
dc.title (題名) The Development and Application of Digital Twin: Taking Manufacturing Industry as an Exampleen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (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.		zh_TW