可控變形區域和模具磨耗之最佳化研究 —以避震器之鋁冠鍛件為例

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蘇惠貞(Hui-Zhen Su) 查詢紙本館藏

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機械工程學系

論文名稱

可控變形區域和模具磨耗之最佳化研究 —以避震器之鋁冠鍛件為例
(Optimization of controllable deformation zone and die wear of aluminum crown forgings for shock absorber assembly)

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至系統瀏覽論文 (2026-6-30以後開放)

摘要(中)

本論文以製造自行車鋁冠鍛件為研究，由於傳統的製程設計容易發生鍛件缺陷之問題，故此研究提出一種具有可控制變形區(CDZ)的模具毛邊設計，並將數值模擬與實驗設計(DOE)結合以利最佳化製程參數，以最大限度地優先保留鍛件的完整性，同時探討模具磨耗。
本文先以田口(Taguchi)方法進行實驗設計，探討三個設計因子:胚料直徑(D)、胚料長度(L)和模具毛邊設計(F)，對訊噪比(SRN)進行最佳化設計，再結合灰色關聯分析(GRA)得出最佳化之參數設計，另外加以探討利用反應曲面法(RSM)的Box-Behnken設計，對於三個目標反應參數:模具平均磨耗深度(S)、成型負荷(T)和鍛造最後成形時模具與工件之間的距離(C)，進一步得到最佳化之製程參數。根據實驗設計分析結果，指出最佳設計因子為:D=40mm、L=205mm和F=CDZ 1。進而將最佳化之設計因子通過FEA，分別探討在微觀鍛流線(Flow line)的分佈與成形負荷、應力、應變和溫度以及模具設計之影響呈現。為了準確地驗證RSM分析的參數，進行了數值分析和實驗驗證之比對，呈現出高度的合理一致性。

摘要(英)

This dissertation focuses on manufacturing aluminum crown forgings for shock absorber assembly. Due to the traditional process design is prone to forging defects, this research proposes a die flash design with a controllable deformation zone (CDZ), and finite element analysis (FEA) was combined with response surface method (RSM) to optimize the processing parameters with the aim of minimizing the die wear while the integrity of forgings should be prioritized preserved.
This article first uses Taguchi method for design of experiments(DOE), discussing three design factors: billet diameter (D), billet length (L) and die flash design (F), use signal-to-noise ratio (SRN) and gray relational analysis (GRA) to get the optimized parameter design, and discuss the Box-Behnken design using the RSM for three target response parameters: the mean die wear depth (S), the forming load (T) and the distance between the die and the workpiece (C) during the final forging forming process further optimize the process parameters. According to the results of the DOE, it is pointed out that the best design factors are: D=40mm, L=205mm and F=CDZ 1. Furthermore, the optimized design factors are analyzed through the results of FEM, and the influences of flow line and forming load, stress, strain and temperature as well as die design are discussed respectively. In order to accurately verify the parameters of the RSM analysis, a comparison between numerical analysis and experimental verification was carried out, showing a high degree of reasonable consistency.

關鍵字(中)

★ 可控變型區
★ 有限元素分析
★ 實驗設計
★ 熱鍛
★ 模具磨耗
★ 鋁冠鍛件

關鍵字(英)

★ Controllable deformation zone
★ Crown for shock absorber assembly
★ Design of experiments
★ Finite element analysis
★ Hot forging
★ Wear depth

論文目次

摘要 I
ABSTRACT II
誌謝 IV
目錄 V
圖目錄 VIII
表目錄 XII
第一章緒論 1
1-1 前言 1
1-2 研究動機與方法 2
第二章文獻回顧 4
2-1 鋁及鋁合金特性與分類 4
2-1-1鋁合金特性 4
2-1-2 鋁合金分類 4
2-2 鍛造加工製程與模具磨耗 6
2-2-1 鍛造加工之分類[4] 6
2-2-2 模具磨耗 9
2-3 有限元素分析與可控制變型區域 12
2-4 品質設計之簡介 13
2-4-1 品質設計之定義[38] 13
2-4-2 品質設計之分類[38] 14
2-4-3 品質設計之程序[38] 16
2-4-4 品質設計之步驟[38] 17
2-4-5 品質設計之田口方法[38] 18
2-4-6 品質設計之反應曲面法[38] 20
2-4-7 實驗設計之相關文獻 24
2-5 灰色關聯分析 25
第三章材料與實驗設置 28
3-1 實驗材料 28
3-2 實驗設備 30
第四章最佳化製程設計 38
4-1 鍛件之製程設計 38
4-1-1 初始鍛造製程設計 38
4-1-2 有限元素分析之參數 44
4-1-3 可控制變形區域之模具設計 52
4-2 實驗設計 53
4-2-1 單目標最佳化―田口法 53
4-2-2 多目標最佳化―灰色關聯法 64
4-2-3 反應曲面法 68
第五章模擬結果與實驗驗證 78
第六章結論 88
參考文獻 90

參考文獻

[1] Ozturk, F., Sisman, A., Toros, S., Kilic, S., & Picu, R. C. Influence of aging treatment on mechanical properties of 6061 aluminum alloy., Materials and Design 31 2010;972–975.
[2] ASM Handbook , Property and selection：Nonferrous Alloys and Pure Metals, ASM,Vol.2 9th pp.1-236, 1979.
[3] 許源泉，鍛造學理論與實習，三民書局，1990
[4] 金屬工業發展中心，鍛造技術，經濟部國際貿易局，1981
[5] 周俊宏，金屬二次加工Technology roadmap專題研究-沖壓、鍛造，經濟部，2002
[6] Gronostajski, Z., Kaszuba, M., Hawryluk, M., Zwierzchowski, M., A review of the degradation mechanisms of the hot forging tools. Archives of Civil and Mechanical Engineering 2014;528-539.
[7] Shen, L., Zhou, J., Xiong, Y.-B., Zhang, J.-S., & Meng, Y., Analysis of service condition of large hot forging die and refabrication of die by bimetal-layer weld surfacing technology with a cobalt-based superalloy and a ferrous alloy., Journal of Manufacturing Processes, 2018; 731–743.
[8] Hawryluk, M., Ziemba, J., Lubrication in hot die forging processes. Proc Inst Mech Eng Part J J Eng Tribol 2019;233/5: 663–675.
[9] Barrau, O., Boher, C., Vergne, C., Rezai-Aria, F. Investigation of friction and wear mechanism of hot forging tool steels. 6th int tooling conference (Karlstadt) 2002.
[10] Baumel, A., Seeger, T. Material data for cyclic loading. Supplement 1. Materials science monographs vol 61 Elsevier Science Publishers Amsterdam 1990.
[11] Gronostajski, Z., Kaszuba, M., Hawryluk, M., Marciniak, M., Zwierzchowski, M., Mazurkiewicz, A, et al. Improving durability of hot forging tools by applying hybrid layers. Metalurgija 2015;54(4):687–90.
[12] Gronostajski, Z., Kaszuba, M., Hawryluk, M, Zwierzchowski, M. A review of the degradation mechanisms of the hot forging tools. Arch Civil Mech Eng 2014;14(4):528–39.
[13] Smolik, J. A. Hybrid surface treatment technology for increase of hot forging dies. Arch Metall Mater 2012;57(3):657–64.
[14] Altan, T. Cold and Hot Forging Fundamentals and Application. ASM International. Ohio State University 2005.
[15] Mazurkiewicz, A., Dobrodziej, J. Model of intelligent database in processing of information concering data of constitution of surface layers. 4th CONTECSI - International Conference on Information Systems and Technology Management 2007.
[16] Dinesh Babu, P., Prasannakumar, B., Marimuthu, P., Mishra, R. K., & Ram Prabhu, T. Microstructure, wear and mechanical properties of plasma sprayed TiO2 coating on Al–SiC metal matrix composite. Arch Civil Mech Eng 2019;19(3):756–67.
[17] Mazurkiewicz, A., & Smolik, J. The innovative directions in development and implementations of hybrid technologies in surface engineering. Arch Metall Mater 2015;60(3):2161–72.
[18] Gronostajski Z, Hawryluk M, Kaszuba M, Marciniak M, Niechajowicz A, Polak S, et al. The expert system supporting the assessment of the durability of forging tools. Int J Adv Manuf Technol 2016; 82:1973–91.
[19] Hawryluk, M., 2016, Methods of analysis and increasing durability of forging tools used in hot die forging processes, monographic publishing series. Problems of operation and machine construction, ISBN 978-83-7789-410-1, Ed.Scientific, ITE – PIB, Radom.
[20] Taylan, A., Gracious, N., Gangshu, S., 2005, ASM metals handbook, vol. 14. p.337–338.
[21] Hawryluk, M., Kaszuba, M., Gronostajski, Z., Polak, S., & Ziemba, J., Identification of the relations between the process conditions and the forging tool wear by combined experimental and numerical investigations. CIRP Journal of Manufacturing Science and Technology. 2020; 87-93.
[22] Gronostajski Z, Marcin K, Sławomir P, Maciej Z, Adam N, Marek H. The failure mechanisms of hot forging dies. Mater Sci Eng A 2016; 657:147–160.
[23] Behrens, BA. Finite element analysis of die wear in hot forging processes. CIRP Ann – Manuf Technol 2008; 57:305–308.
[24] Archard, J. F. Contact and rubbing of flat surfaces. J. Appl. Physics 1953, 24, 981–988.
[25] Bayer, R. G. Mechanical wear fundamentals and testing. Marcel Dekker Inc 2004.
[26] Ghorbani, S., Kopilov, V.V., Polushin, N.I., Rogov, V.A. Experimental and analytical research on relationship between tool life and vibration in cutting process. Arch Civil Mech Eng 2018; 18/3: 844–862.
[27] Thiyagu, M., Karunamoorthy, L., Arunkumar, N. Thermal and tool wear characterization of graphene oxide coated through magnetorheological fluids on cemented carbide tool inserts. Arch Civil Mech Eng 2019; 19/4:1043–1055.
[28] Abachi, S., Akkok, M., Gokler, M. l. Wear analysis of hot forging dies. Tribol Int 2010; 43:467–473.
[29] Ghaei, A., Movahhedy, M. R. Die design for the radial forging process using 3D FEM. J of Mater Process Technol 2007; 182:534–539.
[30] Liu, Y., Wu, Y., Wang, J., Liu, S. Defect analysis and design optimization on the hot forging of automotive balance shaft based on 3D and 2D simulations. Int J Adv Manuf Technol 2018; 94:2739–2749.
[31] Langner, J., Stonis, M., Behrens, B. A. Investigation of a moveable flash gap in hot forging. J of Mater Process Technol 2016; 231:199–208.
[32] Eyercioglu, O., Kutuk, M. A., Yilmaz, N. F. Shrink fit design for precision gear forging dies. J of Mater Process Technol 2009; 209:2186–2194.
[33] He, H., Huang, S., Yi, Y., Guo, W. Simulation and experimental esearch on isothermal forging with semi-closed die and multistage- hange speed of large AZ80 magnesium alloy support beam. J of Mater Process Technol 2017; 246:198–204.
[34] Wan, K. T., Ho, K. L, Soo, K. B. Multi-stage cold forging and experimental investigation for the outer race of constant velocity joints. Mater Des 2013; 49:368–385.
[35] Kroiß, T., Engel, U., Merklein, M. Comprehensive approach for process modeling and optimization in cold forging considering interactions between process, tool and press. J Mater Process Technol 2013; 213:1118–1127.
[36] Mori, K., Nakano, T., 2016. State-of-the-art of plate forging in Japan. Prod. Eng. 10 (1),81–91.
[37] QForm, finite element simulation software data base.
[38] 葉怡成，實驗計畫法-製程與產品最佳化，五南出版社，2001
[39] Ahn, S., Montero, M., Odell, D., Roundy, S., Wright, P. K. Anisotropic material properties of fused deposition modeling ABS. Rapid Prototyp J 2002;8:248–57.
[40] Chin, K. A., Leong, K. F., Chua, C. K., Chandrasekaran, M. Investigation of the mechanical properties and porosity relationships in fused deposition modelling‐ fabricated porous structures. Rapid Prototyp J 2006; 12:100–5.
[41] Onwubolu, G. C., Rayegani, F. Characterization and optimization of mechanical properties of ABS parts manufactured by the fused deposition modelling process. Int J Manuf Eng 2014; 2014:13.
[42] Anitha, R., Arunachalam, S, Radhakrishnan, P. Critical parameters influencing the quality of prototypes in fused deposition modelling. J Mater Process Technol 2001; 118:385–8.
[43] Chohan, J. S., Singh, R. Enhancing dimensional accuracy of FDM based biomedical implant replicas by statistically controlled vapor smoothing process. Prog Addit Manuf 2016; 1:105–13.
[44] Wang, C. C., Lin, T., Hu, S. Optimizing the rapid prototyping process by integrating the Taguchi method with the Gray relational analysis. Rapid Prototyp J 2013.
[45] Lee, B. H., Abdullah, J., Khan, Z. A. Optimization of rapid prototyping parameters for production of flexible ABS object. J Mater Process Technol 2005; 169:54–61.
[46] Nancharaiah, T. Optimization of process parameters in FDM process using design of experiments. Int J Emerg Technol 2011; 2:100–2.
[47] Sahu, R. K, Mahapatra, S. S., Sood, A. K. A study on dimensional accuracy of fused deposition modeling (FDM) processed parts using fuzzy logic. J Manuf Sci & Prod 2013;13(183).
[48] Huynh, H.N., Nguyen, A.T., Ha, N. L., Thu, T., Thai, H. Application of fuzzy taguchi method to improve the dimensional accuracy of fused deposition modeling processed product. Int Conf Syst Sci Eng 2017:107–12.
[49] Verran, G. O, Mendes, R. P. K, Valentina, D. L. V. O. DOE applied to optimization of aluminum alloy die castings. J of Mater Process Technol 2008; 200:120–125.
[50] Syrcos, G. P. Die casting process optimization using Taguchi methods. J of Mater Process Technol 2003; 135:68–74.
[51] Qi, Z., Wang, X., Chen, W. A new forming method of straight bevel gear using a specific die with a flash. Int J Adv Manuf Technol 2019; 100:3167–3183.
[52] Chen, W. C., Nguyen, M. H, Chiu, W. H., Chen, T. N, Tai P. H. Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO. Int J Adv Manuf Technol 2016; 83:1873–1886.
[53] Lin, B. T, Kuo, C. C. Application of the fuzzy-based Taguchi method for the structural design of drawing dies. Int J Adv Manuf Technol 2011; 55:83–93
[54] Liu, J., Cui, Z. Hot forging process design and parameters determination of magnesium alloy AZ31B spur bevel gear. J of Mater Process Technol 2009; 209:5871–5880.
[55] NIST/SEMATECH e-Handbook of Statistical Methods, http://www.itl.nist.gov/div898/handbook/
[56] Deng, J. Introduction to grey system theory. J. Grey Syst. 1989;1:1–24.
[57] Rajeswari, B., Amirthagadeswaran KS. Experimental investigation of machinability characteristics and multi-response optimization of end milling in aluminium composites using RSM based grey relational analysis. Measurement 2017;105:78–86.
[58] Unnikrishna Pillai, J., Sanghrajka, I., Shunmugavel, M., Muthuramalingam, T., Goldberg, M., Littlefair, G. Optimisation of multiple response characteristics on end milling of aluminium alloy using Taguchi-Grey relational approach. Measurement 2018;124:291–8.
[59] Amlana Panda, Ashok Kumar Sahoo, Arun Kumar Rout. Multi-attribute decision making parametric optimization and modeling in hard turning using ceramic insert through grey relational analysis: A case study. Decision Science Letters 5 2016;581–592
[60] Vadde, K. K., Syrotiuk, V. R., & Montgomery, D. C. Optimizing protocol interaction using response surface methodology. IEEE Transactions on Mobile Computing, 2006;5(6), 627–639.
[61] Minitab, Statistical software data base.

指導教授

傅尹坤(Yiin-Kuen Fuh)

審核日期

2021-7-15

推文