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系統識別號 U0026-1908201103113000
論文名稱(中文) 基於本體論之案例式推理系統建立-以面板切割製程為例
論文名稱(英文) A Case-Based Reasoning System Based on Ontology ─ A Case Study of the Panel Cutting Process
校院名稱 成功大學
系所名稱(中) 工程科學系專班
系所名稱(英) Department of Engineering Science (on the job class)
學年度 99
學期 2
出版年 100
研究生(中文) 林沿村
研究生(英文) Yen-Tsun Lin
學號 n9797118
學位類別 碩士
語文別 中文
論文頁數 71頁
口試委員 指導教授-王宗一
口試委員-黃悅民
口試委員-侯廷偉
中文關鍵字 本體論  問答系統  案例自動分類 
英文關鍵字 Ontology  Q & A system  case of automatic classification 
學科別分類
中文摘要 LCD面板切割製程主要是利用切割、裂片、磨邊以及清洗等四個主要動作,針對前段製程(PI / Rub / ODF)來的大板進行尺寸最終化與電路外露化(For IC bonding),以供後續的LCM製程。其中,如何保持各機台運轉的流暢性,端看工程人員對於機台端所產生各式問題的敏感度及處理速度。同時隨著公司的成長,機台系統數量變得龐大而維護工作日漸繁重,而人力的更迭異動亦是一個企業中常見的事情,這均會影響到生產及維護部門的人力安排,以及最重要的人員經驗知識的傳承。
本研究將以某LCD面板製造公司切割製程之異常處理案例,輔以本體論(Ontology)的詞意延伸概念,建立其語意架構,利用領域專家所建立的領域本體論與案例本體論為基礎,進行案例自動化分類與詢答式案例推理系統之建置。在操作使用上,系統能依使用者之自然語言的問題描述,經領域本體論進行關鍵字淬取,以利在案例本體論中找到最近似的歷史案例,同時推薦使用者最適切的問題解決方式,以提高工程師進行問題處理的效率。
本研究最主要的貢獻在於將需要高度依賴人工進行問題判斷與處理的環境中所得之經驗與知識,有系統地保留下來,避免這些隱性的知識資產因人員異動而流失,或是因資訊過於分散而無法有效分享。利用案例自動化分類與詢答式案例推理系統相互搭配,得以讓工程人員們透過知識的累積與分享來提昇技術能力及相關領域知識。經過實測所得數據顯示本論文中所建置的系統能有效地提升工程人員問題處理的效能。
英文摘要 LCD panel cutting process comprises of four major actions, Cutting, Breaking, Grinding and Cleaning, to process the whole board, coming from FEOL (PI / Rub / ODF), for Final Size Setting and Circuit Exposing (For IC bonding) for subsequent LCM process. In the process, how to maintain machines in smooth operations depends on the engineers’ sensitivity to all kinds of machine problems and their problem solving abilities. As the company growths, manufacture machines growth in amount correspondingly, and so as in the load of machine maintenances. To make things even worse, quick workforce changes is a common phenomenon in such business, making the management of manpower difficult and, inevitably, the inheritance of working experience and knowledge virtually impossible.
This study uses the machine problem handling cases in the panel cutting process of a LCD manufacturing company as an example, combined with the concept of word meaning extension by ontology, and, based on expert-established domain ontology and exception ontology, to establishment a semantic structure for auto-classifying problem cases and for a querying-based problem inferring system. The system can accept natural language descriptions of a problem from users, extract keywords by the help of the domain ontology, infer the most similar solved cases in the recent problem solving history, and recommend to the users the most appropriate way for solving the problem in order to improve troubleshooting efficiency of engineers.
The main contribution of this study is to retain engineers’ experience and knowledge of problem solving which is highly human-oriented and to avoid implicit knowledge assets losing due to workforce changes and ineffective knowledge sharing because of information fragmentation. Using such accumulated experience and knowledge and the querying-based problem inferring system, engineers can share technical skills to enhance their problem solving efficiency as well as domain knowledge. Measured data from some experiments shows that the system, built in this study, can significantly improve the problem solving ability and efficiency of engineers in a LCD manufacturing company.
論文目次 中文摘要 I
Abstract II
誌 謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 導論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究方法與流程 3
1.4 論文架構 5
1.5 研究成果與貢獻 7
第二章 相關研究與文獻探討 9
2.1 本體論基本定義 9
2.2 本體論的應用與優勢 18
2.3 中文斷詞系統 20
2.4 文件自動分類系統 25
2.5 問答系統 27
第三章 系統分析與架構 30
3.1 研究構想 30
3.2 研究架構 33
3.3 資料收集與前處理系統 37
3.4 案例自動分類系統 42
3.5 詢答式案例推理系統 49
第四章 系統建置與驗證 55
4.1 實作環境 55
4.2 系統驗證方法 57
4.3 系統驗證結果 60
4.3.1 案例自動分類系統驗證 60
4.3.2 詢答式案例推理系統驗證 63
第五章 結論與未來研究方向 66
5.1 研究結論 66
5.2 未來研究方向 68
參考文獻 69
參考文獻 中文
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英文
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