臺灣博碩士論文加值系統

影響到塑料產品幾何精度的翹曲變形是射出成型技術的固有。理論上，當翹曲值過高時，很難能把零件組裝在一起。所以，需要縮小翹曲值，使得塑料成品具有外形精度高及極佳質量。
本研究運用數值模擬技術跟田口方法調查最佳參數設置於使用射出成型技術之塑料防護眼鏡前架，包括融化溫度、包裝壓力、注射速度及包裝時間。本實驗在田口方法基礎上進行研究三種聚碳酸酯 (wonderlite, lupoy 和 panlite)， 四個程序參數的九種設置，每個參數設定於三級。因此，各種材料的九個翹曲值是利用odlex3D 軟件來模擬。根據S/N 比率，可以獲得控制塑料防護眼鏡前架的物理性質之適當材料及最佳參數設置。本研究使用誤差分析 (ANOVA) 指出每個參數對翹曲值的貢獻。最後結果顯示塑料品的翹曲值約是 0.4934 毫米。

Warpage which affects the geometrical accuracy of plastic products is inherent in the injection molding process. Theoretically, in case of the warpage values of the assembly parts are high; it is difficult to assemble the parts together. Hence, there is a need to minimize the warpage value so that the finished plastic product can be produced with high accuracy in shape and quality.
Applied the numerical simulation techniques and Taguchi method, this study would like to investigate the optimum setting of process parameters, including melting temperature, packing pressure, injection velocity and packing time, for the injection molding process of plastic safety glasses’ chassis frame. The experiment is conducted with three types of polycarbonate (Wonderlite, Lupoy and Panlite) and nine different settings of four process parameters with three levels which are designed based on Taguchi Method. Accordingly, for each material, nine warpage values are predicted by using Moldex3D software. From the signal-to-noise (S/N) ratio, the proper material and optimum setting of process parameters to control the physical properties of plastic chassis frames are obtained. The analysis of variance (ANOVA) is also employed in this study to find out the contribution of each parameter to the warpage value. The final result shows that the warpage value of the plastic product is about 0.4934 mm.

ACKNOWLEDGEMENT i
ABSTRACT ii
摘要 iii
TABLE OF CONTENTS iv
LIST OF TABLES vii
LIST OF FIGURES viii
CHAPTER 1 INTRODUCTION 1
1.1 Overview 1
1.2 Object and objective of study 3
1.3 Scope of study 4
CHAPTER 2 TECHNICAL BACKGROUND 5
2.1 Injection Molding 5
2.1.1 Introduction 5
2.1.2 Material 6
2.1.2.1 Introduction 6
2.1.2.2 Polycarbonate 7
2.1.3 Injection Molding Machine 9
2.1.3.1 Introduction 9
2.1.3.2 Injection Unit 10
2.1.3.3 Clamping Unit 14
2.1.4 Mold 16
2.2 Residual Stress, Shrinkage and Warpage in Injection Molding 22
2.2.1 Residual Stress 22
2.2.1.1 Flow-induced Residual Stress 22
2.2.1.2 Thermal-induced Residual Stress 23
2.2.2 Causes of Shrinkage 23
2.2.2.1 Part Thickness 23
2.2.2.2 Holding Pressure 24
2.2.2.3 Melt Temperature 24
2.2.2.4 Injection Rate 25
2.2.3 Causes of Warpage 25
2.2.3.1 Uneven Cooling of the Part 25
2.2.3.2 Part Geometry Asymmetry 26
2.2.3.3 Variable Packing 27
2.2.3.4 Molecular or Fiber Orientation Due to Flow 28
2.3 Design of Experiments via Taguchi Method: Orthogonal Arrays 28
2.3.1 Introduction 28
2.3.2 Summary of Taguchi Method 29
2.3.3 Taguchi Loss Function 29
2.3.4 Determining Parameter Design Orthogonal Array 30
2.3.5 Signal to Noise Ratio Analysis 31
2.3.6 Advantages and Disadvantages 32
CHAPTER 3 METHODOLOGY AND EXPERIMENT 33
3.1 General Approach 33
3.2 Numerical Simulation Technique 34
3.2.1 Model 35
3.2.1.1 Some Notations in Design 35
3.2.1.2 The Model Built 37
3.2.2 Mesh 37
3.2.3 Material 39
3.2.4 Manufacturing Conditions 40
3.2.4.1 Selecting Injection Molding Machine 40
3.2.4.2 Setting Injection Molding Process Parameters 40
3.2.5 Analysis 41
3.2.6 Result of Warpage 43
3.3 Application of Taguchi Method 44
3.3.1 Factors and Levels 44
3.3.2 Taguchi Orthogonal Array 46
3.3.3 Experiment Results and S/N Ratios for Warpage 47
3.3.4 S/N Response for Warpage 48
CHAPTER 4 RESULTS AND DISCUSSION 51
4.1 Optimum Settings of Injection Molding Process Parameters for Chassis Frame of Plastic Safety Glasses 51
4.2 Warpage 52
4.2.1 Warpage Value 52
4.2.2 Allocation of Warpage 54
4.2.3 Relationships between Warpage and Each Examined Process Parameter 56
4.2.4 The ANOVA (Analysis of Variance) for Warpage 60
CHAPTER 5 CONCLUSION AND FUTURE WORKS 65
5.1 Conclusion 65
5.2 Future Works 66
REFERENCES 67

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