本論文研究以熱塑性聚氨酯(Thermoplastic Polyurethanes, TPU)強化聚甲醛(Polyoxymethylene, POM)之複合材料在不同射出成型(Injection Molding)製程加工參數下，如TPU混煉比例、熔融溫度、保壓壓力、保壓時間、射出速度與冷卻時間，找出多品質最佳製程參數水準之組合。利用田口方法(Taguchi Method)中的直交表設計實驗，並以田口方法中的主效果分析與變異數分析理論得到單一品質之製程最佳參數水準組合，再將實驗所得之各品質數據，分別利用主成份分析法(Principal Component Analysis)、灰關聯分析法(Grey Relation Analysis)以及反應曲面法(Response Surface Methodology)結合模擬退火法(Simulated Annealing) 三種不同方法各別找出多品質最佳製程參數水準之組合，並做多品質數據之比較。研究結果顯示，若同時考量拉伸強度、硬度與彎曲強度三項多品質特性時，由反應曲面法結合模擬退火法所求得之最佳條件其實驗結果較佳，其參數條件為TPU添加10 wt.%、熔融溫度200℃、保壓壓力40 MPa、保壓時間1.2 s、射出速度40 mm/s與冷卻時間14.75 s，證實本研究所規劃之方法能對POM/TPU複合材料之多品質有效的提升。

In this study, we use thermoplastic polyurethanes (TPU) to reinforce polyoxymethylene (POM) for POM/TPU composites and try to obtain the optimal parameters for multiple qualities of injection molding, including TPU ratio, melt temperature, packing pressure, packing time, injection speed and cooling time. First of all, we use the orthogonal array of Taiguchi method to design the experiments and analyze the data by factor effects and analysis of variance (ANOVA), to get the optimal parameters of single quality. Then, we aim to determine the optimal parameters for multiple qualities using three different methods, principal component analysis (PCA), grey relation analysis (GRA) and response surface methodology (RSM) with simulated annealing algorithm (SAA). We compare qualities of tensile strength, hardness and flexure strength by the three methods, and the method of RSM with SAA is better than the others. The optimal parameters are 10 wt % TPU ratio, melt temperature 200℃, packing pressure 40 MPa, packing time 1.2 seconds, injection speed 40 mm/s and cooling time 14.75 seconds. The results also prove that the three methods can efficiently enhance the three multiple qualities of POM/TPU composites.

[1] K. Palanivelu, S. Balakrishnan and P. Rengasamy, “Thermoplastic Polyurethane Toughened Polyacetal Blends,” Polymer Testing, Vol. 19, pp. 75–83, 2000.
[2] C. L. Liu, R. Zhou, D. Wu and L. H. Chen, “Study on Toughening of POM by TPU,” Polyurethane Industry , Vol. 23, No. 4, 2008.
[3] G. Xie, K. Geng, P. Wang, R. M. Tang, X. I. Jiang and X. L. Fan, “Study on Increasing The Toughness of Blends from Polyoxymethylene and Thermo Plastic Polyurethane Elastomer,” Journal of Natural Science of Heilongjiang University, Vol. 25, No. 2, 2008.
[4] M. Mehrabzadeh and D. Rezaie, “Impact Modification of Polyacetal by Thermoplastic Elastomer Polyurethane,” Journal of Applied Polymer Science, Vol. 84, No. 14, pp. 2573-2582, 2002.
[5] X. L. Gao, C. Qu and Q. Fu, “Toughening Eechanism in Polyoxymethylene/Thermoplastic Polyurethane Blends,” Polymer International, Vol. 53, No. 11, pp. 1666-1671, 2004.
[6] W. H. Tang, H. H. Wang, J. Tang and H. L. Yuan, “Polyoxymethylene/Thermoplastic Polyurethane Blends Compatibilized with Multifunctional Chain Extender,” Journal of Applied Science, Vol. 127, No. 4, pp. 3033-3039, 2013.
[7] D. H. Zhang, M. He, J. B. Guo and S. H. Qin, “Mechanical, Thermal and Dynamic Mechanical Properties of Long Glass Fiber-Reinforced Thermoplastic Polyurethane/Polyoxymethylene Composites,” Polymer Composites, Vol. 35, No. 10, pp. 2067-2073, 2014.
[8] J. C. Viana, N. Billon and A. M. Cunha, “The Thermomechanical Environment and the Mechanical Properties of Injection Moldings,” Polymer Engineering and Science, Vol. 12, pp. 1522-1533, 2004.
[9] M. H. Chung, “Study on Weld-Line of ABS Thin-Wall Injection Molding Parts,” Master Thesis, Department of Mechanical Engineering, Chung Yuan Christian University, 2001.
[10] R. P. Koster, “Importance of Injection Molding Parameters for Mechanical Performance of Cold Flow Weld Lines,” Journal of Injection Molding Technology, Vol. 3, No. 3, pp. 154-158, 1999.
[11] P. L. Su, “Study on the Influence of Molding Conditions on the Properties of Injection Molded Nanocomposites of Nylon6/Fluoromica,” PhD. Dissertation, Department of Mechanical Engineering, Chung Yuan Christian University, 2004.
[12] T. Erzurumlu and B. Ozcelik, “Minimization of Warpage and Sink Index in Injection-molded Thermoplastic Parts Using Taguchi Optimization Method,” Materials and Design, Vol. 27, pp. 856-861, 2006.
[13] L. I. Tong, C. T. Su and C. H. Wang , “The Optimization of Multi- response Problems in the Taguchi Method,” International Journal of Quality and Reliability Management, Vol. 14, pp. 367-380, 1997.
[14] Z. H. Xu, S. C. Wang, Z. W. Zhang, T. S. Chin and C. K. Sung, “ Optimization of Magnetizing Parameters for Multipole Magnetic Scales Using the Taguchi Method,” IEEE Transactions on Magnetics, Vol. 51, No. 1, 2015.
[15] Z. H. Xu, S. C. Wang, Z. W. Zhang, T. S. Chin, and C. K. Sung, “ Optimization of Magnetizing Parameters for Multipole Magnetic Scales Using the Taguchi Method,” IET Science, Measurement and Technology, Vol. 9, No. 5, pp. 628-635, 2015.
[16] H. M. Hasanien, “Design Optimization of PID Controller in Automatic Voltage Regulator System Using Taguchi Combined Genetic Algorithm Method,” IEEE Systems Journal, Vol. 7, No. 4, pp. 825-831, 2013.
[17] C. T. Su and L. I. Tong, “Multi-Response Robust Design by Principle Component Analysis,” Total Quality Management, Vol. 8, No. 6, pp. 409-416, 1997.
[18] J. Antony, “Multi-Response Optimization in Industrial Experiments Using Taguchi’s Quality Loss Function and Principal Component Analysis,” Quality and Reliability Engineering International, Vol. 16, pp. 3-8, 2000.
[19] J. S. Shih, Y. F. Tzeng and J. B. Yang, “Principal Component Analysis for Multiple Quality Characteristics Optimization of Metal Inert Gas Welding Aluminum Foam Plate,” Materials and Design, Vol. 32, No. 6, pp. 1253-1261, 2011.
[20] D. J. Burke and M. J. O’Malley, “A Study of Principal Component Analysis Applied to Spatially Distributed Wind Power,” IEEE Transactions on Power Systems, Vol. 26, No. 4, pp. 2084-2092, 2011.
[21] Q. Hu, P. Su, D. Yu and J. Liu, “Pattern-Based Wind Speed Prediction Based on Generalized Principal Component Analysis,” IEEE Transactions on Sustainable Energy, Vol. 5, No. 3, pp. 866-874, 2014.
[22] S. Shokralla, J. E. Morelli and T. W. Krause, “Principal Components Analysis of Multifrequency Eddy Current Data Used to Measure Pressure Tube to Calandria Tube Gap,” IEEE Sensors Journal, Vol. 16, No. 9, pp. 3147-3154, 2016.
[23] R. Adalarasan, M. Santhanakumar and A. S. Sundaram, “Optimization of Weld Characteristics of Friction Welded AA 6061-AA 6351 Joints Using Grey-principal Component Analysis (G-PCA),” Journal of Mechanical Science and Technology, Vol. 28, No. 1, pp. 301-307, 2014.
[24] Y. S. Trang , S. C. Juang and C. H. Chang , “The Use of Grey-Based Taguchi Methods to Determine Submerged Arc Welding Process Parameters in Hardfacing,” Journal of Materials Processing Technology, Vol. 128, No. 3, pp. 1-6, 2002.
[25] C. L. Lin, “Use of the Taguchi Method and Grey Relational Analysis to Optimize Turning Operations with Multiple Performance Characteristics,” Materials and Manufacturing Processes, Vol. 19, No. 2, 2004.
[26] C. S. Huang, “Application of Grey Relational Analysis, Taguchi's Method and Response Surface Methodology in Multi-objective Quality Characterization Optimization,” Master Thesis, The Department of Asia-Pacific Industrial and Business Management, National University of Kaohsiung, 2009.
[27] N. Natarajan and R. M. Arunachalam, “Optimization of Micro-EDM with Multiple Performance Characteristics Using Taguchi Method and Grey Relational Analysis,” Journal of Scientific and Industrial Research, Vol. 70, No. 7, pp. 500-505, 2011.
[28] C. Wen, H. Yu, T. Hong, M. Hu, L. Huang, Z. Chen and G. Meng, “Coil Shape Optimization for Superconducting Wind Turbine Generator Using Response Surface Methodology and Particle Swarm Optimization,” IEEE Transactions on Applied Superconductivity, Vol. 24, No. 3, 2014.
[29] B. H. Lee, J. P. Hong and J. H. Lee, “Optimum Design Criteria for Maximum Torque and Efficiency of a Line-Start Permanent-Magnet Motor Using Response Surface Methodology and Finite Element Method,” IEEE Transactions on Magnetics, Vol. 48, No. 2, pp. 863-866, 2012.
[30] C. Versèle, O. Deblecker and J. Lobry, “A Response Surface Methodology Approach to Study the Influence of Specifications or Model Parameters on the Multiobjective Optimal Design of Isolated DC–DC Converters,” IEEE Transactions on Power Electronics, Vol. 27, No. 7, pp. 3383-3395, 2012.
[31] F. Bertocci, A. Fort, L. Shahin, M. Mugnaini and R. Berni, “Assessment and Optimization for Novel Gas Materials Through the Evaluation of Mixed Response Surface Models,” IEEE Transactions on Instrumentation and Measurement, Vol. 64, No. 4, pp. 1084-1092, 2015.
[32] H. C. Chen, J. C. Lin, Y. K. Yang and C. H. Tsai, “Optimization of Wire Electrical Discharge Machining for Pure Tungsten Using A Neural Network Integrated Simulated Annealing Approach,” Expert Systems with Applications, Vol. 37, No. 10, pp. 7147-7153, 2010.
[33] K. M. El-Naggar, M. R. AlRashidi, M.F. AlHajri and A. K. Al-Othman, “Simulated Annealing Algorithm for Photovoltaic Parameters Identification,” Solar Energy, Vol. 86, No. 1, pp. 266-274, 2012.
[34] C. Y. Lin, “Application of Simulated Annealing to Optimize Parameters of the QUAL2E Model,” Master Thesis, Department of Bioenvironmental Systems Engineering, National Taiwan University, 2005.
[35] C. F. F. Costa, A. T. de Albuquerque and M. G. F. Costa, “Luminance Optimization in Closed Environments by Simulated Annealing,” IEEE Latin America Transactions, Vol. 8, No. 3, pp. 229-235, 2010.
[36] 吳復強編著，品質改善的冺器：產品穩健設計-田口方法之原理與應用，全威圖書股份有限公司，2005。
[37] 李輝煌編著，田口方法之品質設計的原理與實務，高立圖書有限公司，2008。
[38] H. F. Hotelling, “The Application of Electronic Computers to Factor Analysis,” Educational and Psychological Measurement, Vol. 20, pp. 141-151, 1933.
[39] 鄧聚龍編著，灰色系統基本方法，華中理工大學出版社， 1987。
[40] S. Kirkpatrick and M. P. Vecchi, “Optimization by Simulated Annealing,” Science, Vol. 220, No. 4598, pp. 671-680, 1983.
[41] H. Z. Su, “Parameters Setting in Simulated Annealing,” Master Thesis, Department of Mechanical Engineering, National Taiwan University of Science and Technology, 1997.
[42] E. Poupaert and Y. Deville, “Simulated Annealing with Estimated Temperature,” AI Communications, Vol. 13, No. 1, pp. 19-26, 2000.