臺灣博碩士論文加值系統

摘　　要
設備維修對於機械設備具有延長使用壽命，避免因為零件發生損壞造成連鎖的損失。而複雜度高的重要零件維修上，需依靠工程師的經驗來決定所需之維修製程，針對少量多樣性的渦輪葉片維修型態，其維修製程的規劃階段，不同的破壞特徵會有不同的維修製程。
本研究針對此種製程規劃特性，建立一渦輪葉片維修製程規劃系統，依照此種規劃製程型態，著手分析破壞特徵並分類，提出一個採用專家系統常用的案例庫及模糊語言集運算，嘗試將工程師的規劃經驗由案例庫保留下來，並且分析決定維修製程的關鍵因素，做為找尋相似案例及決定加工程序。為達成此目的，著手建立一個雛形系統，作為實現上述目的之驗證，首先將渦輪葉片出現的破壞特徵作分類，相關修護程序也依製程不同作分類編碼，並且使用模糊語言集來作為判斷相關修護案例的比對，採用Case-based reasoning的理論發展此系統，並將決定出演算流程，規劃分析儲存相關資訊的資料庫，嘗試和產品資料管理系統整合。本研究以某科技公司為對象，進行渦輪葉片維修製程規劃雛形系統的驗證及討論。

Abstract
Maintenance makes machine life long more and gets no loss about a chain reaction on part broken. Repair a part that has high complex and is important. It need engineer experience to decide its maintenance process plan. For turbine blade maintenance style that has various type and a small quantity. Different broken feature have different maintenance process in the maintenance process planning stage.
This thesis creates a system for this property maintenance on the process planning system on the Maintenance of turbine blades. Analyzing blade broken feature and classifying the feature to bring up a case-based reasoning and fuzzy set operation that usually see in expert systems. It uses case-based databases to save engineer experiences and analysis to decide critical maintenance process factors. The critical factors can help find out similarity case and modulate a newer case. It needs to create a proto-type system for these purposes. The first, classifying turbine blades broken feature and coding the repair process for different maintenances. The second, using fuzzy set language to determine case’s similarity and finding out algorithm. Integrating product data management system and the system. The research uses a company as case study to test and verify the proto-type system.

目錄
目錄I
圖目錄III
表目錄V
第1章 導論1
1.2 背景1
1.3 研究目的2
1.4 研究方法3
第2章 文獻回顧5
2.1 產業電子化架構5
2.2 渦輪葉片破壞修護方式8
2.3 電腦輔助製程規劃與專家知識系統9
2.4 模糊理論12
2.5 案例式推理法13
2.6 結論15
第3章 渦輪葉片維修製程系統規劃17
3.1 收集維修製程18
3.2 破壞特徵分類21
3.2.1 定義渦輪葉片各部位之名稱21
3.2.2 破壞特徵分類21
3.3 維修製程分類22
3.4 系統規劃27
第4章 渦輪葉片維修製程系統建立30
4.1 建立案例權重矩陣30
4.2 建立選取演算流程35
4.3 規劃製程管理資料庫38
4.4 建立製程產生程式41
第5章 系統驗證42
第6章 結論53
6.1 研究結論53
6.2 研究貢獻及未來發展54
參考文獻56
附錄A 模糊理論簡介58
A.1 模糊推論58
A.2 三角形模糊數58
A.3解模糊60
A.3.1推論後得到的是模糊集合60
A.3.2 推論後得到明確的輸出值61
附錄B 案例式推理法的推理流程62

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