微型擠壓絲攻應用於316L不鏽鋼攻牙暨製程參數之實驗研究

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题名:	微型擠壓絲攻應用於316L不鏽鋼攻牙暨製程參數之實驗研究
作者:	許永翰;Hsu, Yung-Han
贡献者:	機械工程學系
关键词:	擠壓絲攻;Box-Behnken;變異數分析;最佳化;反應曲面;Form tap;Box-Behnken;Analysis of variance(ANOVA);Optimization;Response surface
日期:	2022-08-30
上传时间:	2022-10-04 12:15:51 (UTC+8)
出版者:	國立中央大學
摘要:	本文使用M1.2擠壓絲攻對316L不鏽鋼試片進行內螺紋攻牙實驗，探討刀具製程參數對於内螺紋攻牙品質特性的影響，並達成參數最佳化的目標。刀具製程參數選用M1.2擠壓絲攻之外徑、刀具寬、齒根徑及無效牙長，且被視為品質因子並規劃實驗設計。內螺紋攻牙品質特性選用攻牙產生的最大扭矩值及牙型填充率的實驗結果作為討論的指標。為了建構二階反應曲面的迴歸模型，故使用四因子三水準的Box-Behnken實驗設計法，規劃28組實驗點並據以實施攻牙實驗。使用統計軟體Minitab對實驗的結果進行變異數分析，以建立最大扭矩值與牙型填充率之迴歸模型，並討論品質因子對於品質特性的效應。最後，以限制最佳化問題進行優化，並以望小最大扭矩值為目標函數，牙型填充率為限制條件求得最佳化解，再透過實驗進行驗證確定最佳化解之準確度。結果顯示，最大扭矩值及牙型填充率的迴歸模型具有足夠的準確度。;In this paper, the M1.2 form tap was used to conduct internal thread tapping experiments on 316L stainless steel specimens, investigate the influence of tool process parameters on the quality characteristics of internal thread tapping, and complete the parameter optimization. The tool process parameters were selected as M1.2 form tap outer diameter, tool-width, tooth root diameter, and chamfer length, and were considered as quality factor planning experiment design. For the quality characteristics of internal thread tapping, the maximum torque value generated by the tapping and the experimental results of the thread filling rate is used as indicators for discussion. To construct the regression model of the second-order response surface, according to the Box-Behnken experimental design method with four factors and three levels, 28 sets of the tapping experiment were designed. Analysis of variance (ANOVA) based on the experiment results established the regression equation of the thread filling rate and the maximum torque by using Minitab software and discussed the effect of the four quality factors on the two quality characteristics. Finally, the optimization is conducted by constrained optimization problem and the maximum torque value is the objective function, and the thread filling rate is the constraint to obtain the optimal solution. Subsequently, the accuracy of the optimal solution is validated by the tapping experiment. The results show that the regression model has a certain level of accuracy.
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