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研究生:陳建霖
研究生(外文):Chien-Lin Chan
論文名稱:整合Moldflow與基因演算法於射出成型模具冷卻水道位置最佳化
論文名稱(外文):Cooling Channels Location Optimization of Injection Molding Using Integration of Moldflow and Genetic Algorithm
指導教授:吳俊瑩吳俊瑩引用關係
指導教授(外文):Chun-Yin Wu
學位類別:碩士
校院名稱:大同大學
系所名稱:機械工程學系(所)
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
論文頁數:196
中文關鍵詞:基因演算法射出成型模具最佳化冷卻水道
外文關鍵詞:Genetic algorithmInjection moldingOptimizationCooling channel
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射出成型模具的冷卻水道設計,一般都依賴設計人員的工作經驗以及試誤法的程序來設計冷卻水道。經由多次的測試雖能找出符合設計的需求,但對於精度高或形狀複雜性高的產品卻是無法保證。近年來,電腦輔助工程分析技術已被廣泛的應用於各種的領域之中,有助於提升改善複雜且高精度要求的設計。本研究的目的便是運用基因演算法作為最佳化的搜尋工具,並整合CAE模流分析軟體Moldflow搜尋射出成型模具冷卻水道最佳化之配置。本研究採用數個測試方程式驗證程式架構的正確性與執行效率,接著將本程式架構整合模流分析軟體Moldflow應用於冷卻水道位置之最佳化。從兩個設計案例之執行結果,證明本篇研究在射出成型模具的冷卻水道系統設計,能有效提供設計者選擇不同的冷卻水道配置,提高冷卻水道的設計效率,進而提升產品品質與降低成本耗費,增加經濟效益。
The cooling channels design for injection molding usually depends on the designer’s experiences or the process of trial-and-error. Even though the designer could find out the design fitting the requirements through several trials, it still cannot guarantee that the results are good enough specially for high precision component or complicated sharp product.
In recently years, the computer-aided engineering (CAE) has been generally applied in product development for various fields. It contributes for enhancing design ability of complicated and high precision product. The purpose of this study is to find out the optimal arrangement of cooling channels of injection molding by integration of the genetic algorithms for optimization search and the Moldflow software for injection molding analysis.
In order to verify the architecture and performance of optimization program using genetic algorithms (GA), several test functions are utilized to check the accuracy and execution efficiency of developed program. Then the developed GA program was integrated with Moldflow software in optimization of cooling channels location. From the results of two case studies, it was shown that the cooling channels design system implemented in this study could offer designer with different options in selection the arrangement of cooling channels for injection molding. The developed architecture can enhance the design efficiency of cooling channels, upgrade product quality, lower development cost and increase economic benefits.
(ENGLISH CONTENTS)
CHINESE ABSTRACT i
ENGLISH ABSTRACT ii
ACKNOWLEDGEMENTS iii
CONTENTS iv
LIST OF FIGURES vii
LIST OF TABLES x
Chapter 1 Introduction 1
1.1 Preface 1
1.2 Introduction of Plastic Injection Molding 5
1.3 Review of Literature 9
1.3.1 Optimized Cooling Channel Design 9
1.3.2 Genetic Algorithms 11
1.4 Motive and Purpose of Study 12
Chapter 2 Genetic Algorithms 16
2.1 Introduction 16
2.2 Theory of Genetic Algorithms 19
2.2.1 Influences of Reproduction on Fitness Values 20
2.2.2 Influences of Crossover on Fitness Values 21
2.2.3 Influences of Mutation on Fitness Values 22
2.3 Organizations and Structure of Genetic Algorithms 23
2.3.1 Basic Organization of Genetic Algorithms 23
2.3.2 Niche Scheme for Genetic Algorithms 39
2.3.3 Elitism Strategy of Genetic Algorithms 40
2.3.3.1 Determination of Similarity 41
2.3.4 Structure of Genetic Algorithms 42
2.4 Verification of Test Function 44
Chapter 3 Structure of Genetic Algorithms Applied to Optimized Location Design for Cooling Channel of Injection Mold 53
3.1 Introduction 53
3.2 Analysis Model of Cooling Theory Applied by Injection Mold 54
3.2.1 Introduction to Cooling Analysis 54
3.2.2 Analysis on Cooling Theory 56
3.2.2.1 Integral Equation with Boundary Element Method 57
3.2.2.2 Definition of Mold Boundary Condition 61
3.3 Genetic Algorithms Applied to Optimized Location Design for Cooling Channel 62
3.3.1 Design of Location of Cooling Channel 62
3.3.2 Modification of Infeasible Region 63
3.3.3 Determination of Number Cooling Channels 64
3.3.4 Determination of Cooling Channel Similarity 69
3.3.5 Definition of Fitness Value 71
3.4 Structure Integration of Commercial Moldflow Analysis Software 74
Chapter 4 Results and Discussions 76
4.1 Execution of Optimization Design Case (1) 76
4.2 Results of Optimization Design Case (1) 79
4.3 Execution of Optimization Design Case (2) 88
4.4 Results of Optimization Design Case (2) 91
Chapter 5 Conclusions and Future Studies 99
5.1 Conclusions 99
5.2 Future Studies 100
REFERENCES 102

(中文目錄)
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章 緒論 1
1.1 前言 1
1.2 塑膠射出成型簡介 4
1.3 文獻回顧 7
1.3.1 冷卻水道最佳化設計 7
1.3.2 基因演算法 8
1.4 研究動機與目的 9
第二章 基因演算法 12
2.1 簡介 12
2.2 基因演算法之理論基礎 14
2.2.1 複製對適應值之影響 16
2.2.2 交配對適應值之影響 16
2.2.3 突變對適應值之影響 17
2.3 基因演算組織與架構 18
2.3.1 基因演算法之基本組織 18
2.3.2 利基於基因演算法之應用 31
2.3.3 基因演算法之精英策略 32
2.3.3.1 相似度之判斷 33
2.3.4 基因演算法之架構 34
2.4 測試方程式之驗證 36
第三章 基因演算法應用於射出成型模具冷卻水道位置最佳化設計之架構 44
3.1 簡介 44
3.2 射出成型模具之冷卻理論分析模式 45
3.2.1 冷卻分析簡介 45
3.2.2 冷卻理論分析 46
3.2.2.1 邊界元素法之積分方程式 46
3.2.2.2 模具邊界條件之定義 51
3.3 基因演算法應用於冷卻水道位置最佳化設計 52
3.3.1 冷卻水道位置之設計 52
3.3.2 非可行解區域之修正 53
3.3.3 冷卻水道數量之判斷 54
3.3.4 冷卻水道相似度之判斷 58
3.3.5 適應值之定義 60
3.4 整合商用模流分析軟體Moldflow之架構 63
第四章 結果與討論 64
4.1 設計案例(一)最佳化設計之執行 64
4.2 設計案例(一)最佳化設計之執行結果 67
4.3 設計案例(二)最佳化設計之執行 76
4.4 設計案例(二)最佳化設計之執行結果 79
第五章 結論與未來展望 86
5.1 結論 86
5.2 未來展望 87
參考文獻 88
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