博碩士論文 105423019 詳細資訊




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姓名 邱奕華(Yi-Hua Chiu)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 即時串流資料品質綜效架構之研發:以工業蒸汽鍋爐感測設備為例
(A Study of Multi-dimensional Data Quality Framework for Online Data Stream: A Case of Industrial Steam Boiler Sensing Equipment)
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檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2023-6-30以後開放)
摘要(中) 在現今資訊化的時代下,資料品質之良窳對於企業營運具有重大且關鍵的影響,在工業領域中,工業感測設備串流資料的品質所扮演的角色亦是如此。然而,現有品質控制之常見方式,主要著重於錯誤偵測與遺漏值偵測,即僅針對資料產出的結果做考慮,卻忽略了在即時串流資料上可能也會引發相異的品質問題。因此,本研究旨在以串流資料的性質以及工業感測設備應用的訴求之下,提出一全面性的即時串流資料品質綜效架構(a Multi-dimensional Data Quality framework for online Data Stream, 簡稱MDQDS)。同時,透過這一架構所建立的三個品質構面指標—準確性、完整性、一致性,以及其具體測試規則協助設備操作人員能即時地從不同面向來掌握設備資料的各種品質。在實務應用上,本研究依據所提出的架構,實作出一個應用程式MDQDSS(MDQDS System)以幫助設備操作人員能適時且有效的提升與維護工業感測設備資料之品質,並以工業蒸汽鍋爐感測設備的串流資料為例。並且,為了驗證本研究提出的架構與所實作出之系統的可行性,本研究亦將MDQDSS應用於紡織工業蒸汽鍋爐之感測設備資料中,來展示系統功能與使用情形最後,針對現有的運用與研究限制進行討論,並提出未來研究的可能方向。
摘要(英) In this information era, the quality of data is significant to enterprises. In industry, the quality of streaming data of industrial Sensing Equipment also plays an important role in decision-making. However, the existing methods of streaming data quality control focus on error detection and missing values detection, which aim at neglect the quality problems arises from the data processes. Therefore, this research aims to propose a comprehensive framework of the quality of streaming data of industrial Sensing Equipment, termed Multi-dimensional Data Quality framework for online Data Stream (MDQDS). This framework is based on online state, especially focusing on the demand of the system characteristics of industrial sensing equipment and streaming data. Simultaneously, by the three quality dimensions—accuracy, completeness, and consistency—built by this framework, MDQDS can help observers from different views to handle a variety of online streaming data qualities. In the practical application, according to the proposed framework, this research implements an application, MDQDSS (MDQDS System), to help observers to increase and maintain the quality of streaming data of industrial sensing equipment. Moreover, to verify the feasibility of the proposed framework and the implemented system, this research applies MDQDS to the industrial steam boiler sensing equipment in H textile factory to demonstrate the proposed system and the test situation. Finally, discussion and suggestions are presented for the existing application and this research proposes the probable direction of the future work.
關鍵字(中) ★ 資料品質
★ 串流資料
★ 資料窗格
★ 工業感測設備資料
★ 工業蒸汽鍋爐
關鍵字(英) ★ Data Quality
★ Data Stream
★ Data Window
★ Industrial Sensing Equipment Data
★ Industrial Steam Boilers
論文目次 摘要 i
Abstract ii
致謝 iii
圖目錄 vi
表目錄 vii

第一章 緒論 1
1.1. 研究背景 1
1.2. 研究動機與問題 3
1.3. 研究目的與預期效益 4
1.4. 論文架構 5

第二章 文獻探討 6
2.1. 工業感測設備的串流資料 7
2.1.1. 工業感測設備資料 7
2.1.2. 串流資料的定義 7
2.1.3. 串流資料的架構 8
2.1.4. 串流資料的運用與相關議題 9
2.2. 資料品質 11
2.2.1. 資料品質的定義 11
2.2.2. 資料品質的衡量方式 12
2.3. 工業感測設備串流資料之現有品質管理方式 15
2.3.1. 品質問題分類 15
2.3.2. 資料品質控制 16
2.3.3. 評論 19

第三章 系統概念與設計 21
3.1. 系統架構 21
3.2. 架構之細部說明 23
3.2.1. 準確性(Accuracy) 23
3.2.2. 完整性(Completeness) 24
3.2.3. 一致性(Consistency) 25
3.3. 流程與功能架構 28
3.3.1. MDQDS:以系統功能觀點探討 28
3.3.2. MDQDS:以系統流程觀點 29
3.3.3. MDQDS:以物件與物件之互動關係 31

第四章 系統實作與展示 33
4.1. 工業蒸汽鍋爐感測設備背景介紹 33
4.2. 系統開發架構與環境 35
4.3. 系統實作與說明 36
4.3.1. 初步設定 39
4.3.2. 系統執行 43

第五章 系統驗證 51
5.1. 信賴度分析 51
5.2. 討論 54
5.3. 研究限制 56

第六章 結論與未來展望 57
6.1. 研究結論與貢獻 57
6.2. 未來展望 57

參考文獻 59
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指導教授 陳仲儼(C.Y. Chen) 審核日期 2018-7-26
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