English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 80990/80990 (100%)
造訪人次 : 41635266      線上人數 : 1362
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋


    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/88408


    題名: 3D列印熱塑性聚酯彈性體之製程研究;Research on manufacturing process of thermoplastic polyester elastomer by 3D printing
    作者: 王善弘;Wang, Shan-Hong
    貢獻者: 機械工程學系在職專班
    關鍵詞: 熱塑性聚酯彈性體;積層製造;熔融沉積成型;田口方法;Thermoplastic polyester elastomer;additive manufacturing;fused deposition molding;Taguchi method
    日期: 2022-01-26
    上傳時間: 2022-07-14 01:20:09 (UTC+8)
    出版者: 國立中央大學
    摘要: 隨著科學技術的發展,新型塑料也不斷的被人們所發掘,且投入在日常生活、工業的開發中廣泛的應用;熱塑性聚酯彈性體(TPEE)被成功開發後,在實際的使用上具有較高的性能,也擁有較高的性價比;和工程塑料相比,擁有較高強度的特點與較長的使用壽命。惟熱塑性聚酯彈性體由於質地軟,不易以機械加工的方式成型,現有成型方法大都使用擠出、注射、吹塑成型,生產前需準備成型所需要的模具與周邊配件;但樣品設計初期至導入量產過程中常會發生設計變更需求,若未能在量產前進行樣品製作、測試,找出需修改的地方而貿然投入模具製作,後續衍生的模具修改需求,所耗費的失敗成本與模具修改等待的時間成本是一筆不小的開支。本文應用積層製造技術(Additive Manufacturing, AM)與熱塑性聚酯彈性體搭配田口方法分析,得到熱塑性聚酯彈性體最佳的彈性能模數。
    綜合上述,本研究是使用熔融沉積成型技術(Fused Deposition Modeling, FDM)列印熱塑性聚酯彈性體,藉由列印設備所能控制的參數獲得最佳彈性能模數。本實驗所使用的製程參數為噴頭直徑、噴頭溫度、層厚高度;以田口式實驗設計,應用L4直交表進行實驗,並且利用變異數分析(Analysis of variance, ANOVA)找出影響結果較顯著的控制因子。經由實驗結果,在彈性能模數方面由品質特性反應表的S/N反應圖顯示出,最佳之組合為噴頭直徑0.6mm、噴頭溫度230°C、層厚高度0.15mm。經由變異數分析找出顯著控制因子,比對品質特性反應表、ANOVA所得參數二者比對最佳化組合的結果相同,如此可驗證實驗準確性。
    ;With the development of science and technology, new plastics are constantly being discovered by people, and they are widely applied in daily life and industrial development; after the successful development of thermoplastic polyester elastomer (TPEE), it has higher performance and good value in practical use. Compared with engineering plastics, it has feature of higher strength and longer lifetime. However, thermoplastic polyester elastomers are not easy to be molded by mechanical processing due to their soft texture. Existing molding methods mostly use extrusion, injection, and blow molding. The molds and peripheral accessories required for molding must be prepared before production. However, the design change requests often occur in the process of initating sample design till mass production. If you fail to conduct sample production and testing before mass production, figure out the places that need to be modified and rush into mold manufacturing, subsequent derivative mold modification needs, the cost of failure and mold failure Modifying the time cost of waiting is not a small expense. This article applies additive manufacturing technology (AM) and thermoplastic polyester elastomer with Taguchi method analysis to obtain the best modulus of resilience of thermoplastic polyester elastomer.
    Based on the above, this study uses Fused Deposition Modeling (FDM) to print thermoplastic polyester elastomers, and obtains the best elastic modulus through the parameters that can be controlled by the printing equipment. The process parameters used in this experiment are nozzle diameter, nozzle temperature, and layer thickness; Taking Taguchi experimental as design, applying L4 orthogonal table for the experiment, and using analysis of variance (ANOVA) to figure out significant control factor which affects the result. Through the experimental results, in terms of elastic modulus, the S/N response diagram of the quality characteristic response table shows that the best combination is nozzle diameter 0.6 mm, nozzle temperature 230°C, and layer thickness 0.15 mm. According to the analysis of variance to find the significant control factors, comparing the quality characteristics response table and the parameters obtained by ANOVA, the results of the optimized combination of the two comparisons are the same, so that the accuracy of the experiment can be verified.
    顯示於類別:[機械工程學系碩士在職專班 ] 博碩士論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML73檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明