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研究生： 金小飛
Septianda Angelica
論文名稱： Digital Twin Design of a Machining Tool for Real-Time Monitoring
Digital Twin Design of a Machining Tool for Real-Time Monitoring
指導教授： 王孔政
Kung-Jeng Wang
口試委員: 何秀青
Mei HC Ho
朱宇倩
Yu-Qian Zhu
學位類別： 碩士
Master
系所名稱： 管理學院 - 管理學院MBA
School of Management International (MBA)
論文出版年： 2020
畢業學年度： 106
語文別： 英文
論文頁數： 44
中文關鍵詞： 數位孿生 、機台監控 、戰情中心 、智慧製造
外文關鍵詞： Digital Twin, Machine Monitoring, Dashboard System, Smart Manufacturing
相關次數： 點閱：297  下載：3 
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  •  上一筆

    • 因應整合切割工具機和即時製造之決策，數位孿生是一項核心技術。 利用數位孿生可以串聯多個獨立的工具機，形成相互連結的系統，提供管理者即時監控機台狀態。本研究提出一套數位孿生之架構，可用於監控僅具低階聯網之傳統工具機， 並以模切機(die cutting machine)為例，評估所提出架構的有效性。此外，本研究也建立戰情中心用以即時控制生產情況。其中，戰情中心主要包含三項功能：即時顯示機台狀況、整體設備之運作效率以及進行訂單之排程。綜言之，本案主要的貢獻為提出一套數位孿生架構，並可應用在聯網技術較低之工具機上，仍可獲致工業物聯網級之智慧製造能力。

    Digital Twin (DT) is a core technology that enables integration between physical cutting machines and real-time manufacturing decisions. DT connects isolated machines to an interconnected system and monitors machine conditions in real-time. In this paper, a DT framework is proposed for the real-time monitoring of conventional machines. This paper presents a DT design of a die cutting machine. A dashboard-based mission center is created to display the real-time condition of the machine. The mission center consists of three main functions: real-time machine monitoring, overall equipment effectiveness, and order scheduling. The present paper proposes a DT framework consisting of conventional machine structure but still has a tolerant level of industrial Internet of things capability.

    摘要 iii Abstract iv Acknowledgement v Content of Table vii Content of Figure viii Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Research Objective 2 1.3 Thesis Structure 3 Chapter 2 Literature Review 4 2.1 Digital Twin 4 2.2 Digital dashboard 8 2.3 Overall equipment effectiveness 9 Chapter 3 Method 11 3.1 Proposed DT framework 11 3.2 Data capturing module 11 3.3 DT intelligent module 15 3.4 DT data module 16 Chapter 4 Experiment and result 18 4.1 Target machine 18 4.2 DT intelligent module 21 4.3 DT data module 24 Chapter 5 Conclusion 29 Appendix. Target machine specification 30 References 31

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