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內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 = = ...

陳楷鈞

內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 = = Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 =/ 陳楷鈞.
其他題名:	Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts /
其他題名:	Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts.
作者:	陳楷鈞
出版者:	雲林縣 :民113.07.,
面頁冊數:	[10], 75面 :圖, 表 ; : 30公分.;
附註:	指導教授: 林瑞璋.
標題:	齒輪塑膠件. -
電子資源:	電子資源

內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 = = Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts /
陳楷鈞

內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 =Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts /Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts.陳楷鈞. - 初版. - 雲林縣 :民113.07. - [10], 75面 :圖, 表 ;30公分.

指導教授: 林瑞璋.

碩士論文--國立虎尾科技大學機械設計工程系碩士班.

含參考書目.

在工業發展的潮流中，製造業面臨著提升生產效率、降低成本以及確保產品品質的挑戰。塑膠射出成形過程中，翹曲變形、熱殘留應力問題影響塑件齒輪與嵌件嵌合處穩定性和壽命。為此，如何優化塑件射出成形製程成為急需解決的問題。本研究的核心目標在於運用數位雲端監控技術，對塑膠齒輪製程及齒輪軸嵌合處進行優化。我們先利用Moldex3D模流分析軟體對製程進行仿真模擬，並使用田口法找出最佳射出參數組合。再透過製程監控，我們將實時監測製程中的溫度及壓力，進一步提高製造效率和產品品質。使用Moldex3D模流分析軟體進行製程模擬，並利用田口法找出最佳射出參數組合。得出的結果是原始組別的預測模溫為44℃(實驗時間:3:19)時，嵌合處變形(翹曲-總位移)為0.048mm，整體變形(翹曲-總位移) 為0.2437mm，翹曲_von-mise應力為98.347mpa，最佳化組別的預測模溫35.6℃(實驗時間:2:57)時，模擬出來的嵌合處變形(翹曲-總位移)為0.036mm，整體變形(翹曲-總位移) 為0.1928mm，翹曲_von-mise應力為87.963mpa，根原始組別比較，嵌合處變形(翹曲-總位移)改善25%，整體變形(翹曲-總位移)改善20%，翹曲_von-mise應力改善10%。原始組別平坦度模擬結果為0.0450mm，最佳化組別為0.0352mm。實際量測顯示原始組別平坦度為0.0496mm，最佳化組別為0.0382mm，誤差分別為9%和7.8%。優化參數有效降低了變形量和熱殘留應力，經變異數分析及回歸分析證實，冷卻時間和保壓時間是關鍵因素。.

(平裝)Subjects--Topical Terms:

1452031
齒輪塑膠件.

內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 = = Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts /
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245 1 0 $a 內嵌入式金屬件與齒輪塑膠件嵌合處優化之數位雲端監控模具應用研究 = $b Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts / $c 陳楷鈞.
246 1 1 $a Research on the Application of Digital Cloud Monitoring Mold for the Optimization of the Mating of Embedded Metal Parts and Gear Plastic Parts.
250 $a 初版.
260 # $a 雲林縣 : $e 國立虎尾科技大學 , $c 民113.07.
300 $a [10], 75面 : $b 圖, 表 ; $c 30公分.
500 $a 指導教授: 林瑞璋.
500 $a 學年度: 112.
502 $a 碩士論文--國立虎尾科技大學機械設計工程系碩士班.
504 $a 含參考書目.
520 3 $a 在工業發展的潮流中，製造業面臨著提升生產效率、降低成本以及確保產品品質的挑戰。塑膠射出成形過程中，翹曲變形、熱殘留應力問題影響塑件齒輪與嵌件嵌合處穩定性和壽命。為此，如何優化塑件射出成形製程成為急需解決的問題。本研究的核心目標在於運用數位雲端監控技術，對塑膠齒輪製程及齒輪軸嵌合處進行優化。我們先利用Moldex3D模流分析軟體對製程進行仿真模擬，並使用田口法找出最佳射出參數組合。再透過製程監控，我們將實時監測製程中的溫度及壓力，進一步提高製造效率和產品品質。使用Moldex3D模流分析軟體進行製程模擬，並利用田口法找出最佳射出參數組合。得出的結果是原始組別的預測模溫為44℃(實驗時間:3:19)時，嵌合處變形(翹曲-總位移)為0.048mm，整體變形(翹曲-總位移) 為0.2437mm，翹曲_von-mise應力為98.347mpa，最佳化組別的預測模溫35.6℃(實驗時間:2:57)時，模擬出來的嵌合處變形(翹曲-總位移)為0.036mm，整體變形(翹曲-總位移) 為0.1928mm，翹曲_von-mise應力為87.963mpa，根原始組別比較，嵌合處變形(翹曲-總位移)改善25%，整體變形(翹曲-總位移)改善20%，翹曲_von-mise應力改善10%。原始組別平坦度模擬結果為0.0450mm，最佳化組別為0.0352mm。實際量測顯示原始組別平坦度為0.0496mm，最佳化組別為0.0382mm，誤差分別為9%和7.8%。優化參數有效降低了變形量和熱殘留應力，經變異數分析及回歸分析證實，冷卻時間和保壓時間是關鍵因素。.
520 3 $a In the trend of industrial development, the manufacturing industry is facing the challenges of improving production efficiency, reducing cost and ensuring product quality. In the process of plastic injection molding, warpage and deformation, and thermal residual stress affect the stability and life of the inserts and gears of plastic parts. Therefore, how to optimize the injection molding process has become an urgent problem. The core objective of this study is to optimize the plastic gearing process and gear shaft insertion using digital cloud monitoring technology. The process is simulated using Moldex 3D mold flow analysis software and the Taguchi method is used to find the optimal combination of injection parameters. Through process monitoring, we will monitor the temperature and pressure during the process in real time to further improve manufacturing efficiency and product quality. The Moldex3D mold flow analysis software was used for process simulation and Taguchi's method was used to find out the optimal combination of injection parameters. The results are 0.048mm of insert deformation (warpage-total displacement), 0.2437mm of all deformation (warpage-total displacement), and 98.347mpa of warpage_von-mise stress for the original group with the predicted mold temperature of 44℃ (experiment time: 3:19), and 0.048mm of insert deformation (warpage-total displacement) and 0.2437mm of overall deformation (warp_von-mise stress) for the optimized group with the predicted mold temperature of 35.6℃ (experiment time: 2:57). At the predicted mode temperature of 35.6°C (experimental time: 2:57) for the optimized group, the simulated inlay deformation (warpage-total displacement) is 0.036mm, the all deformation (warpage-total displacement) is 0.1928mm, and the warpage_von-mise stress is 87.963mpa. Compared with the original group, the inlay deformation (warpage-total displacement) is improved by 25%, the overall deformation (warpage-total displacement) is improved by 20%, and the warpage_von-mise stress is improved by 10%. The simulation result of the original group flatness is 0.0450mm, and the optimization group is 0.0352mm. The actual measurement shows that the original group flatness is 0.0496mm, and the optimization group is 0.0382mm, with an error of 9% and 7.8% respectively. The optimized parameters effectively reduced the amount of deformation and thermal residual stress. Variance analysis and regression analysis confirmed that the cooling time and holding time were the key factors..
563 $a (平裝)
650 # 4 $a 齒輪塑膠件. $3 1452031
650 # 4 $a 變形優化. $3 1452032
650 # 4 $a 製程管理. $3 1452033
650 # 4 $a 田口法. $3 995557
650 # 4 $a Moldex 3D. $3 1452034
650 # 4 $a Gear Plastic Parts. $3 1452035
650 # 4 $a Deformation Optimization. $3 1452036
650 # 4 $a Process Management. $3 1452037
650 # 4 $a Taguchi Method. $3 995069
856 7 # $u https://handle.ncl.edu.tw/11296/9b9hb9 $z 電子資源 $2 http