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系統識別號 U0026-0609201114295300
論文名稱(中文) 發展具預測能力之通用型設備監控平台
論文名稱(英文) Development of a Generic Equipment Monitoring Platform with Prediction Capabilities
校院名稱 成功大學
系所名稱(中) 製造資訊與系統研究所碩博士班
系所名稱(英) Institue of Manufacturing Information and Systems
學年度 99
學期 2
出版年 100
研究生(中文) 孫瑋志
研究生(英文) Wei-Chih Sun
學號 P96981093
學位類別 碩士
語文別 中文
論文頁數 61頁
口試委員 指導教授-鄭芳田
共同指導教授-洪敏雄
口試委員-楊浩青
中文關鍵字 虛擬機器  資料前處理模組  可抽換式演算法模組  CNC工具機  加工精度預測 
英文關鍵字 v-Machine (Virtual Machine)  Data Pre-Process Module  Pluggable Algorithm Module  CNC Tool  Process Precision Conjecture 
學科別分類
中文摘要 隨著製造科技的日新月異,生產設備也更趨精密。然而,生產設備常因長時間運轉,導使相關零組件老化或故障,進而降低加工產品的品質。因此,在設備監控系統建構預測能力(如錯誤偵測、製造精度推估、剩餘壽命預測等)以確保生產品質相當重要。本研究將發展一種具備預測能力之通用型設備監控平台,稱為v-Machine (Virtual Machine)。v-Machine主要由(1)資料擷取介面,(2)虛擬機核心(Kernel),(3)可抽換演算法模組(Pluggable Algorithm Module, PAM),以及(4)通訊介面等所組成。v-Machine可透過資料擷取介面直接連接裝設於生產設備上的感測器,擷取製造加工時的感測資料。虛擬機核心包含一個資料前處理模組,可以對原始感測資料進行處理與篩選,然後計算出相對應的特徵值 (Indicators);之後,這些特徵值可用來建立預測模型或是傳給可抽換式演算法模組進行加工參數之預測。可抽換式演算法模組乃是將含有演算法的預測模型建置成可抽換的形式而成。我們可以依照應用的需求,動態地載入v-Machine中。而通訊介面可讓v-Machine透過SOAP協定與外部系統交換資料。最後,本研究將v-Machine實際應用於CNC工具機之加工精度預測。實驗測試結果顯示,v-Machine確實能符合各項功能設計需求,並有不錯之效能。
英文摘要 With the advancement of manufacturing technologies, production equipment has become more sophisticated. However, because production equipment is often in long-term operation, some of its components may become aged or broken, thereby reducing the quality of processed products. Therefore, the construction of a predictive capability (such as fault detection, manufacturing precision conjecture, remaining useful life prediction, etc.) in an equipment monitoring system to ensure production quality is very important. This study develops a generic equipment monitoring platform with prediction functionality, called v-Machine (virtual machine). The v-Machine mainly consists of four parts: (1) data acquisition interface, (2) kernel, (3) pluggable algorithm module (PAM), and (4) communication interface. The v-Machine connects to the sensors on production equipment through the data acquisition interface to acquire sensor data during the manufacturing process. The kernel contains a data pre-process module that can process and filter the raw sensor data and compute the corresponding indicators. Then, these indicator data can be used to create conjecture models or fed to the PAM to forecast the process parameters. The PAM is generated by creating the prediction model in a form with a pluggable interface. We can dynamically download a proper PAM to the v-Machine according to the application need. The communication interface can allow the v-Machine to exchange data with other systems through the SOAP protocol. Finally, this study practically applies the v-Machine to the process precision conjecture of CNC tools. Experimental results show that the v-Machine can really meet all the functional design requirements and has a good performance.
論文目次 目錄 i
表目錄 iii
圖目錄 iv
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 3
1.3 論文架構 4
第二章 雲端化運算之設備監控系統框架 5
2.1 以雲端運算為基礎之設備監控系統架構 5
2.2 本地端虛擬機器 (v-Machine) 7
第三章 v-Machine之系統需求分析 9
3.1 v-Machine獨立運作需求 9
3.1.1 資料收集需求分析 10
3.1.2 資料前處理需求分析及預測功能需求分析 10
3.2 v-Machine與外部系統溝通之需求 13
3.2.1 與雲端系統之通訊之需求分析 13
3.2.2 與廠內Web Server溝通之需求分析 15
第四章 v-Machine之核心功能模組設計 16
4.1 系統架構設計 17
4.2 主要預測流程設計 20
4.3 可抽換式演算法模組設計 22
4.4 隨插即用(Plug&Play)之介面設計 27
4.5 資料前處理模組(Data Preprocess Module, DPM) 30
4.6 外部系統通訊功能 34
4.6.1 模型下載與儲存管理 35
4.6.2 雲端建模資訊儲存及本地端模型資訊載入 38
第五章 v-Machine系統實作 42
5.1 部署環境 42
5.2 系統資料來源 43
5.3 整合與測試 44
5.4 效能評估 54
5.4.1 Web GUI資料傳輸效率: 55
第六章 結論與未來工作 58
6.1 研究成果與論文總結 58
6.2 未來研究方向 59
參考文獻 60

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