光碟製程設備中射出成型機遠距維護與故障診斷系統初步探討

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：60

、訪客IP：18.219.207.115

姓名

沈靖傑(Jing-Jie Shen) 查詢紙本館藏

畢業系所

機械工程學系

論文名稱

光碟製程設備中射出成型機遠距維護與故障診斷系統初步探討

相關論文

★ 非等強度分負荷系統之動態負載配置研究	★ 倒傳遞類神經網路學習收斂之初步探討
★ 材料強度退化與累積損傷之探討	★ 累積失效與可靠度關係之探討
★ 碳鋼材料在二氧化硫環境下之腐蝕可靠度行為之探討	★ 動態可靠度模型之探討及其應用
★ 多目標量子搜尋之參數調控演算法	★ 低通濾波器設計可靠度分析
★ 光纖材料之靜力疲勞可靠度分析	★ 競爭策略於系統行為之探討
★ 應用動態可靠度模型預估電解電容器壽命之探討	★ 有限平板多條邊裂紋成長之探討
★ 厚度或折射率變異對窄帶通濾光片之可靠度分析	★ 馬可夫過程的預防維護模型之研究
★ 馬可夫過程在技術成長上之研究	★ 應用馬可夫預防維護模型於維修保養策略之探討

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]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

近年來隨著機械製造技術的進步，因此機械功能性也更顯複雜，對於操作人員而言，擁有高效率的監控與維護的平台才能即時處理機械的突發狀況。以往機械單元若發生故障時，往往必須花費相當大的成本在故障排除的工作上，若能建構一即時診斷環境，提供使用者隨時掌握生產的各項重要資訊，並於異警發生時提供適當的輔助機制，達成網絡化診斷維修之目的，此一課題值得深入探討與研究。
本文提出以網際網路技術（Internet）對於射出成型機進行遠距維護，並利用模糊故障診斷來對設備作故障分析。遠距維護系統是依據案例式推理為基礎，分析射出成型機之異常狀況並建立成案例庫，運用過去案例的經驗，來解決新的問題。
故障模糊診斷是針對案例無法解決故障，則對設備進行診斷分析，找出最有可能發生故障的設備組件，因此利用到故障樹分析法、模糊理論與貝氏定理來建構。

摘要(英)

The manufacturing technology of machines is mature gradually, and to promote the machine functions is becoming more complex gradually in the same time. For the manufacturer, to possess a high-effect remote & maintenance platform, and then to handle machine alarm states in real time are very important. Formerly if the machine unit gave the alarms, manufacturers had to spend a lot of time to eliminate where the machine is breakdown. If it enables to build a real-time diagnosis environment, users might be able to obtain the information of manufacturing in real time. This function can offer users the problem solutions of manufacturing and breakdown. The topic merits discussion and study.
This paper presented a web-based remote diagnosis and maintenance solution for the injection molding machine, and analyzed the breakdown by fuzzy fault diagnosis. The Remote Diagnosis and Maintenance System is based on Case-based Reasoning, and diagnosed the unusual condition of the infection molding machine, and then built the database. The system is used the past case experience to solve the new problem.
The fuzzy fault diagnosis is aimed at the case-based reasoning to be unable to solve the breakdown. Diagnosing the equipment, and discovered the most possibility to case breakdown of the component of the machine. Therefore the diagnosis structure applies the Fault-Tree Analysis, Fuzzy Theorem, and the Bayes Theorem.

關鍵字(中)

★ 模糊診斷
★ 故障樹分析法
★ 射出成型機
★ 案例式推理

關鍵字(英)

★ CBR
★ fuzzy
★ FTA

論文目次

第一章　緒論...........................................................................1
1.1 研究背景與動機..................................................................1
1.2 文獻回顧.................................................................2
1.3 本文架構與大綱...........................................................................4
第二章射出成型機之故障分析.......................................7
2.1 射出成型機介紹..............................................................7
2.1.1 射出成型機構造...........................................................7
2.1.2 射出成型機之動作說明.................................................10
2.2 故障樹分析法（Failure Tree Analysis）.........................12
2.2.1 布林代數（Boolean Algebra）簡介.............................13
2.2.2 故障樹分析法之定性分析............................................14
2.3 射出成型機之故障樹分析...............................................18
2.3.1 射出成型機系統故障樹的建立.....................................18
2.3.2 射出成型機故障樹圖之簡化........................................21
2.4 故障分析流程架構.........................................................23
第三章案例式推論（CBR）..............................................26
3.1 案例式推理（CBR）簡介......................................................29
3.2 案例式推理（CBR）系統之建構.........................................31
3.2.1 蒐集案例資料...........................................................33
3.2.2 製程異常分類...........................................................34
3.2.3 訂定案例推理（CBR）之指標......................................34
3.2.4 建立指標權重...........................................................36
3.2.5 案例間之指標相似度.................................................38
3.2.6 案例相似度公式....................................................39
3.3 案例式推理（CBR）之例子驗證............................................40
第四章遠距維修系統之建構.........................................43
4.1 系統建構環境與工具.........................................................43
4.2 案例庫之建立...................................................................44
4.3 系統操作流程與功能說明..................................................45
4.3.1 使用者登入系統........................................................46
4.3.2 系統主畫面...............................................................46
4.3.3 案例式推理...............................................................47
4.3.4 案例庫管理...............................................................49
第五章模糊故障診斷.......................................................56
5.1 失效單元之判定...............................................................57
5.1.1 模糊矩陣的建立........................................................58
5.1.2 失效單元之判定........................................................59
5.1.3 例子說明..............................................................59
5.2 維護優先次序之估算.........................................................61
5.2.1 貝氏定理..................................................................61
5.2.2 貝氏定理應用於維護優先次序....................................62
5.2.3 例子說明..............................................................62
第六章結論與建議...........................................................65
6.1 結論................................................................................65
6.2 建議................................................................................66
參考文獻................................................................................68
附錄A 層級分析法..................................................................................72
附錄B 模糊理論簡介..................................................................................76
附錄C 射出成型機之維修紀錄表...............................................85

參考文獻

[1] 郭家齊，整合資料探勘與案例式推論於機台故障診斷，國立雲林科技大學碩士論文，2004。
[2] Schank, R.C., Abelson, R.P., Scripts, Plans, Goals and Understanding, Erlbaum, Hillsdate, NJ, 1977.
[3] Schank, R., Dynamic Memory: A Theory of Learning in Computers and Peple, New York: Cambridge University Press, 1982.
[4] Kolodner, J. and Simpson, R. L., “The MEDIATOR: Analysis of an early case-based problem solver,” Cognitive Science, Vol. 13, No. 4, pp. 507-549, 1989.
[5] Bain, W., “Case-based Reasoning: A Computer Model of Subjective ASSESSMENT,” PH.D. Thesis, Department of Computer Science, Yale University, 1986.
[6] Koton, P., “Using Experience in Learning and Problem Solving,” Ph.D. Thesis, Department of Computer Science, MIT, 1989.
[7] Paek, Y. K., Seo, J. and Kim, G. C., “An expert system with case-based reasoning for database schema design,” Decision Support Systems, Vol. 18, pp.83-95, 1996.
[8] Kwong, C. K., Smith, G. F., and Lau, W. S., “Application of Case Based Reasoning in Injection Moulding,” Journal of Materials Processing Technology, Vol. 63 pp.463-467, 1997.
[9] Shi, X. and Yeh, A. G. O., “The Integration of Case-Based systems and GIS in Develop Control,” Environment and Planning B: Planning and Design, Vol. 26, pp.345-364, 1999.
[10] Haque , B. U., Belecheanu, R. A., Barson, R. J. and Pawar, K. S., “Towards the application of case based reasoning to decision-making in concurrent product development (concurrent engineering),” Knowledge-Based System, Vol. 13, pp.101-112, 2002.
[11] Mukhopadhyay, T., Vicinanza, S. S. and Prietula, M. J., “Examining the Feasibility of a Case-Based Reasoning Model for Software Effort Estimation,” MIS Quarterly, Vol. 12, Iss. 2, pp.155-171, 1992.
[12] Ganesan, K., Khoshgoftaar, T. M. and Allen, E. B., “Cased-Based Software Quality Prediction,” International Journal of Software Engineering and Knowledge Engineering, Vol. 10, No. 2, pp.139-152, 2000.
[13] Koiranen, T., Virkki-Hatakka, T., Kraslawski, A. and Nystrom, L., “Hybrid, fuzzy and neural adaptation in case-based reasoning system for process equipment selection,” Computer and Chemical. Engineering, Vol. 22, pp.S977-S1000, 1998.
[14] Yang, J. B. and Yau, N. J., “Integrating Case-Based Reasoning and Expert System Techniques for Solving Experience-Oriented Problems,” Journal of the Chinese Institute of Engineers, Vol. 23, No. 1, pp.83-95, 2000.
[15] 潘俊達，以案例式推理模式之故障診斷專家系統研究，元智大學碩士論文， 1997。
[16] 施育仁，半導體後段製程生產設備維修決策支援系統之研究，國立台北科技大學碩士論文， 2000。
[17] 楊振興，應用案例式推理建構機車維修管理系統，國立台北科技大學碩士論文， 2001
[18] 方榮吉，以案例式推理建構主機板製程分析系統，國立台北科技大學碩士論文， 2001。
[19] 何錦忠，以風險分析為概念的失效模式與效應分析之發展與應用-以汽車零組件業之個案研究，大葉大學碩士論文， 2003。
[20] 李德昌，案例式推理(CBR)對新產品開發與設計作業流程改善之研究，元智大學碩士論文， 2004。
[21] 曾俊仁，模組化即時控制技術於射出成型之應用，國立中山大學碩士論文， 2000。
[22] 蔡林昌，故障樹分析法應用於彈性製造系統組件維護策略之研究，國立中央大學碩士論文， 1997。
[23] Riesbeck, C.K. and Schank, R.C., “From Training to Teaching: Techniques forecast-based ITS”, Intelligent Tutoring System: Education in Design, pp.177-193, New Jersey, 1992.
[24] Fritz, H. G., “Case-Based Reasoning Applying Past Experience to NewProblems”, Information System Management, pp.77-80, Spring, 1993.
[25] Medhbi, M., and Owrang, O., “Case Discovery in Case-Based Reasoning”, Information System Managements, pp.74-78, Winter, 1998.
[26] Ralph, Barletta, “An Introduction to Case-Based Reasoning”, AI Expert, pp.43-49, August, 1991.
[27] Schank, R., Dynamic Memory: A Theory of Learning in Computers and People, New York: Cambridge University Press, 1982.
[28] 陳俊賓，案例式推理在橋樑上部結構工程評選之應用，國立
台灣科技大學碩士論文， 1997。
[29] Kolodner, J., “Case-Based Reasoning,” Morgan Kaufmann Publishers, Inc., 1993.
[30] Saaty, T. L., “ The Analytic Hierarchy Process ”, McGraw-Hill, New York, 1980.
[31] Saaty, T. L. and Vargas L. G., “Uncertainty & Rank Order in the Analytic Hierarchy Process ”, European Journal of Operationals Research, Vol. 32, No.2, pp.107-117., 1987.
[32] Saaty,T. L., “Group Decision Making and the AHP”, in:Golden, B. L. and Wasil, E. (eds.), The Analytic Hierarchy Process: Applications and Studies, Springer-verlag, New York, pp.59-67., 1989.
[33] Saaty, T. L., “Fundamentals of Decision Making and Priority Theory ”, RWS publication., 1994.
[34] Zadeh, L. A., “Fuzzy sets”, Information and Control ,Vol. 8, pp. 338-353., 1965.
[35] Dubois, D. and Prade, H., Fuzzy Sets and System: Theory and Application, Academic Press Inc, 1980
[36] Zadeh, L. A., “The concept of a linguistic variable and its application to approximate reasoning I, II, III, ” Information Science ,Vol. 8, pp.199-251 , pp.301-357；Vol. 9 , pp. 43-80, 1975.

指導教授

王國雄(Kuo-Shong Wang)

審核日期

2006-7-18

推文