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研究生: 謝旻軒
Hsieh, Min-Hsuan
論文名稱: 發展應用於工具機產業之先進製造雲
Development of an Advanced Manufacturing Cloud for Machine Tools
指導教授: 鄭芳田
Cheng, Fan-Tien
共同指導教授: 洪敏雄
Hon, Min-Hsiung
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 製造資訊與系統研究所
Institute of Manufacturing Information and Systems
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 73
中文關鍵詞: 雲製造雲端運算工具機先進製造雲智能化功能預測模型
外文關鍵詞: Cloud Manufacturing, Machine Tool, Cloud Computing, Advanced Manufacturing Cloud, Prediction Model
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  • 雲製造所指的是將分散式的製造資源封裝成雲端服務,使其可支援製造相關的活動。與直接使用雲端運算資源相比,雲製造是一種較進階的雲端運算應用。本論文開發完成一個雲製造平台:先進製造雲(Advanced Manufacturing Cloud, AMC)。先進製造雲提供許多製造相關的雲端服務,可幫助使用者執行一些工具機的智能化活動,例如,收集工具機加工資料到雲端、在雲端建立預測模型、從雲端將預測模型下載到工廠端以執行預測應用、透過雲端服務推薦合適的加工工具機或刀具、透過雲端服務提供虛擬工具機功能等。本論文首先描述AMC的架構設計,然後說明AMC核心功能之設計與實作。為了建置完成一個AMC的雛型,本研究將雲端服務部署於Windows Azure公有雲平台上。最後,本研究將AMC應用於合作廠商的工具機以進行整合測試與效能評估。測試結果驗證了AMC對促進工具機智能化的有效性。

    Cloud manufacturing refers to encapsulating distributed manufacturing resources into cloud services to support manufacturing activities. Compared to direct usage of cloud computing resources, cloud manufacturing is a more advanced application of cloud computing. In this thesis, a cloud manufacturing platform, called AMC (Advanced Manufacturing Cloud), is developed. The AMC provides several manufacturing-related cloud services which can facilitate the users to conduct intelligent activities for machine tools, such as collecting and uploading machining data of machine tools to the cloud, creating prediction models in the cloud, downloading prediction models from the cloud to factories for performing prediction applications, recommending suitable machine tools or cutting tools by cloud services, and providing virtual machine tool functions via cloud services. This thesis presents the architecture design of the AMC first. Then, the design and implementation of the AMC’s core functions are described. To create a prototype of the AMC, the cloud services are deployed on the Windows Azure public cloud platform. Finally, the AMC is applied to the machine tools provided by a cooperative company so as to conduct integrated tests and performance evaluation. Testing results validate the effectiveness of the AMC in facilitating the intelligence of machine tools.

    中文摘要 英文摘要 誌謝 目錄 iv 表目錄 vii 圖目錄 viii 第 一 章 緒論 1 1.1 研究背景 1 1.2 動機與目的 4 1.3 論文架構 6 第 二 章 先進製造雲系統框架設計 7 2.1 先進製造雲系統需求 7 2.1.1 雲端系統需求 7 2.1.2 工廠端系統需求 8 2.2 先進製造雲系統架構設計 8 2.2.1 雲端系統 9 2.2.2 工廠端系統 13 第 三 章 核心功能機制設計 15 3.1 建置智慧型雲端運算服務通用方法設計 15 3.1.1 程式開發階段 16 3.1.2 雲端部署 17 3.2 模型建立雲端服務設計 18 3.3 資料蒐集雲端服務設計 19 3.3.1 資料蒐集服務之設計概念 19 3.3.2 資料蒐集服務運作流程設計 19 3.3.3 資料蒐集計畫XML Scheme設計 21 3.3.4 資料蒐集計畫GUI設計 23 3.3.5 資料蒐集報告XML Schema設計 24 3.4 支援多人同時建模機制設計 30 3.4.1 支援多人同時建模機制之設計概念 30 3.4.2 支援多人同時建模機制架構設計 31 3.4.3 單人建模運作流程設計 33 3.4.4 支援多人同時建模機制流程設計 34 3.5 自動縮放運算資源機制設計 38 3.5.1 自動縮放運算資源機制之概念設計 38 3.5.2 自動縮放運算資源機制架構設計 39 3.5.3 自動縮放運算資源機制運作流程設計 46 第 四 章 系統整合測試與效能評估 48 4.1 實驗設定(EXPERIMENT SETUP) 48 4.1.1 測試環境軟硬體規格 49 4.2 測試腳本(TESTING SCENARIOS) 50 4.2.1 Scenario 1:資料蒐集服務測試 50 4.2.2 Scenario 2:多人同時建模機制測試 52 4.2.3 Scenario 3:不同CPU核心數對建模時間的影響 58 4.2.4 Scenario 4:舊架構與新架構建模時間比較 59 4.2.5 自動縮放運算資源測試 61 第 五 章 結論 69 5.1 論文總結 69 5.2 研究成果 69 5.3 未來研究方向 71 參考文獻 72

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