| 研究生: |
陳煬智 Yang-Zi Chen |
|---|---|
| 論文名稱: |
有限元素法與反應曲面法對旋轉鍛造萬向接頭之最佳化分析 |
| 指導教授: |
葉維磬
Wei-Ching Yeh |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系 Department of Mechanical Engineering |
| 論文出版年: | 2019 |
| 畢業學年度: | 107 |
| 語文別: | 中文 |
| 論文頁數: | 138 |
| 中文關鍵詞: | 旋轉鍛造 、有限元素分析 、萬向接頭 、反應曲面法 |
| 外文關鍵詞: | cold rotary forging, FEM, universal cross joint, Response Surface Methodology |
| 相關次數: | 點閱:16 下載:0 |
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本文利用有限元素軟體Deform-3D進行旋轉鍛造萬向接頭模擬分析,研究設計參數對填充率、最大成形力與應變均勻度的影響。本文之設計參數包含旋轉鍛造加工製程參數及對胚料預成形之參數設計等四個因子。胚料預成形設計參數包含胚料高度H和胚料上端面半徑R;旋轉鍛造加工製程參數包含上模具傾斜角γ以及下模每轉進給率S。
首先經由中心點實驗確定適用二階模型迴歸,再透過最陡坡度法選定較佳的中心點,最終採用適合建構二階反應曲面之Box-Behnken四因子三水準的設計建立共25組模擬,並使用統計軟體Minitab依Deform-3D有限元素分析的結果進行迴歸分析,透過迴歸分析建立二階多項式預測模型。
將本文所建立的品質特性預測方程式與有限元素模擬的結果進行驗證,其結果顯示預測模型具有精確度。並以Minitab求得填充率望大,成形力望小時之最佳化解,再透過模擬進行驗證確定最佳化結果的精確性。
For this study, using a FE model by a software named Deform-3D on cold rotary forging of a universal cross joint. The purpose is to realize that the influence of design factors about filling rate, maximum forging load and equivalent strain uniformity.
The four factors in the design include the work-piece geometry and the rotary forging process parameters. The work-piece geometry such as workpiece height H, the diameter upon the workpiece R and the rotary forging process parameter such us the process parameter with feed amount of per revolution S, and inclination angle of the upper die γ.
First, by the design of center point making sure that the model is suitable for second order regression. Through the steepest-descent method to find a better point to be new center point. Then the experiment adopts 25 groups of analysis with the Box-Behnken design. Using the Minitab software to do the regression analysis and develop the predicted equations.
By doing so, it’s expected to using the FEM model and surface response methodology to find the optimum design of the maximum filling rate and the minimum forging load. In this paper, quality characteristics prediction equation established with the results of finite element simulations can verify the results that the prediction model with considerable accuracy.
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