購買設(shè)計(jì)請充值后下載，，資源目錄下的文件所見即所得，都可以點(diǎn)開預(yù)覽，，資料完整，充值下載就能得到。。?！咀ⅰ浚篸wg后綴為CAD圖，doc,docx為WORD文檔，【有不明白之處，可咨詢QQ:1304139763】
耳機(jī)塑料注塑模具設(shè)計(jì) 摘 要 塑料工業(yè)是當(dāng)今世界上增長最快的工業(yè)門類之一 而注塑模具是其中發(fā)展較 快的種類 因此 研究注塑模具對了解塑料產(chǎn)品的生產(chǎn)過程和提高產(chǎn)品質(zhì)量有很 大意義 注射模技術(shù)的不斷發(fā)展需要越來越多的工藝流程 注射成型過程中最重 要的問題是模具的正確設(shè)計(jì) 從根本上說 注射模具包括澆口和澆注系統(tǒng) 另一部分是放置頂出系統(tǒng) 模 具零件是在分型面被定位的 注射模具型腔選擇等設(shè)計(jì)計(jì)算要求掌握加工材料 注射機(jī)和模具等方面的準(zhǔn) 確知識 模具的制造成本隨著型腔數(shù)目的增加而增加 而相關(guān)的加工費(fèi)用減少了 一個(gè)給定的模具零件的生產(chǎn)周期取決于壁厚 注射速度 收縮率 模內(nèi)材料的冷 卻時(shí)間 冷卻的效能及必要的輔助時(shí)間 如壓力持續(xù)時(shí)間 排氣時(shí)間及延遲時(shí)間 等 本設(shè)計(jì)介紹了注射成型的基本原理 特別是單分型面注射模具的結(jié)構(gòu)與工作 原理 對注塑產(chǎn)品提出了基本的設(shè)計(jì)原則 詳細(xì)介紹了冷流道注射模具澆注系統(tǒng) 溫度調(diào)節(jié)系統(tǒng)和頂出系統(tǒng)的設(shè)計(jì)過程 通過本設(shè)計(jì) 可以對注塑模具有一個(gè)初步 的認(rèn)識 注意到設(shè)計(jì)中的某些細(xì)節(jié)問題 了解模具結(jié)構(gòu)及工作原理 關(guān)鍵詞 塑料模具 參數(shù)化 分型面 澆注系統(tǒng) 模具型腔 I THE PLASTIC INJECT MODLE DESIGN ABSTRACT plastic industry is in the world grows now one of quickest industry classes but casts the mould is development quick type therefore the research casts the mold to understand the plastic product the production process and improves the product quality to have the very big significance The continuing development of injection mold technology demands more and more of the processes The most important problem in the process of injection molding is undoubtedly the correct design of injection mold Basically the injection mold consists of two halves One mold half contains the sprue bushing and runner system the other half houses the ejection system The molded part is located at the parting line To set up a calculation conceiving the choice of cavities in an injection mold requires accurate knowledge of the matrrial to be processed of the injection molding machine and of the molds The mold costs increase with the rising number of cavities and the relative machine costs decrease The production time required for a given molded part depends on the wall thicknes the injection speed the recovery rate the time required to coll the molded material the cooling capacity of the mold and the necessary incidental time such as duration of pressure holding time ejection time delay time ect This design introduced the injection takes shape the basic principle specially single is divided the profile to inject the mold the structure and the principle of eork to cast the product to propose the basic principle of design Introducted in detail the cold flod channel injection evil spirit mold pours the system the temperature contral system and goes against the system the design process and has given the explanation to the mold intensity request Through this design may to cast the mold to have a preliminary understanding notes in the design certain detail question understands the mold structure and the principle of work Through to the PROGRAM study may establish the simple components the components storehouse thus effective enhancement eorking II efficiency KEY WORDS The plastic mold the parameterization inlays divides the profile III 目 錄 前 言 1 第一章 制件的結(jié)構(gòu)與工藝性分析 2 1 1 制件相關(guān)信息 2 1 2 材料的相關(guān)性質(zhì) 3 1 2 1 基本特性 3 1 2 2 主要用途 3 1 2 3 成型特點(diǎn) 3 1 3 塑件的脫模斜度 4 1 4 塑件的尺寸精度及表面質(zhì)量要求 4 第二章 初選注射機(jī) 6 2 1 計(jì)算塑件體積和最大投影面積 6 2 2 選擇壓力機(jī) 6 2 3 確定型腔數(shù)目 7 第三章 模具設(shè)計(jì) 9 3 1 型腔的分布設(shè)置 9 3 2 分型面的確定 9 3 3 澆口的確定原則 10 3 4 澆注系統(tǒng)的確定 11 3 4 1 主流道的設(shè)計(jì) 11 3 4 2 分流道的設(shè)計(jì) 12 3 4 3 冷料穴的設(shè)計(jì) 13 3 4 4 澆口的相關(guān)參數(shù)選擇 14 3 5 成型零部件的結(jié)構(gòu)設(shè)計(jì) 14 3 5 1 型腔的結(jié)構(gòu)設(shè)計(jì) 14 3 5 2 型芯的結(jié)構(gòu)設(shè)計(jì) 15 3 6 模具成型零部件尺寸計(jì)算 15 3 5 1 計(jì)算成型零部件尺寸要考慮的因素 16 3 5 2 制件尺寸的公差轉(zhuǎn)換 16 3 5 3 成型零部件尺寸計(jì)算 17 IV 3 7 模架的選用 20 3 7 1 模架型號的確定 20 3 7 2 模架具體尺寸的確定 21 3 8 結(jié)構(gòu)零部件的設(shè)計(jì) 22 3 8 1 支承板的設(shè)計(jì) 22 3 8 2 墊塊的設(shè)計(jì) 22 3 8 3 定模座板和動(dòng)模座板的設(shè)計(jì) 22 3 8 4 導(dǎo)柱的設(shè)計(jì) 23 3 8 5 導(dǎo)套的設(shè)計(jì) 24 3 8 6 設(shè)計(jì)導(dǎo)柱導(dǎo)套需要注意的事項(xiàng) 24 3 9 推出機(jī)構(gòu)的設(shè)計(jì) 24 3 9 1 推桿的設(shè)計(jì) 25 第四章 冷卻系統(tǒng)的設(shè)計(jì) 28 4 1 冷卻水孔直徑的確定 28 4 2 冷卻水回路的布置原則 28 第五章 注射機(jī)的相關(guān)校核 29 5 1 注射機(jī)額定注射量的校核 29 5 2 注射壓力的校核 29 5 3 鎖模力的校核 29 5 4 模具安裝尺寸的校核 30 5 41 噴嘴尺寸校核 30 5 4 2 模具厚度校核 30 5 5 開模行程的校核 31 結(jié) 論 32 謝 辭 33 參考文獻(xiàn) 34 0 前 言 塑料工業(yè)是新興的工業(yè) 是隨著石油工業(yè)的發(fā)展因應(yīng)運(yùn)而生的 目前塑料制 件幾乎已經(jīng)進(jìn)入一切工業(yè)部門以及人民日常生活的各個(gè)領(lǐng)域 塑料工業(yè)又是一個(gè) 飛速發(fā)展的工業(yè)領(lǐng)域 塑料作為一種新的工程材料 其不斷被開發(fā)與應(yīng)用 加之 成型工藝的不斷成熟 完善和發(fā)展 極大的促進(jìn)了塑料成型方法的研究與運(yùn)用和 塑料模具的開發(fā)與制造 隨著工業(yè)塑料制件和日用塑料之間的品種和需求量日益 增加 這些產(chǎn)品的更新?lián)Q代的周期越來越短 因此對塑料的品種 產(chǎn)量和質(zhì)量都 提出了越來越高的要求 對塑料制件提出高要求的同時(shí)意味著對塑料模具提出了 很高的要求 因?yàn)槟＞呤撬芰瞎I(yè)生產(chǎn)中重要的工藝設(shè)備 因此模具設(shè)計(jì)顯得越 來越重要 塑料模具的設(shè)計(jì)是模具制造中的關(guān)鍵工作 通過合理設(shè)計(jì)制造出來的模具不 僅能順利的成型高質(zhì)量的塑件 還能簡化模具的加工過程和實(shí)施塑件的高效率生 產(chǎn) 從而達(dá)到降低生產(chǎn)成本和提高附加價(jià)值的目的 近幾年來塑料成型工藝迅速發(fā)展 塑料模具種類不斷增加 結(jié)構(gòu)也更為復(fù)雜 在該套模具的設(shè)計(jì)中采用的是一模四腔的模具結(jié)構(gòu) 該套模具的澆口采用的是側(cè) 澆口 側(cè)澆口又稱標(biāo)準(zhǔn)澆口 這種澆口一般開設(shè)在分型面上 塑料熔體內(nèi)側(cè)或外 側(cè)注入型腔 其截面形狀多為矩形 改變澆口的寬度與厚度可以調(diào)節(jié)熔體的剪切 速率及澆口的凍結(jié)時(shí)間 這類澆口可以根據(jù)塑件的形狀特征選擇其位置 加工和 修正方便 普遍用于中小型塑件的多型腔模具 且對各種塑料的成型適應(yīng)性均較 強(qiáng) 其澆口截面小 減少了澆注系統(tǒng)塑料的消耗量 同時(shí)去除澆口容易 且不留 明顯痕跡 因此塑件的表面不受損傷 不致因澆口痕跡而影響塑件的表面質(zhì)量與 美觀效果 該套模具的工作原理是當(dāng)注射結(jié)束時(shí) 模具在開模力的作用下從 D D 分型面分型 當(dāng)動(dòng)模向后移動(dòng)一定距離后推出機(jī)構(gòu)開始工作 推桿推動(dòng)推件板把 塑 件從型芯上推下 完成整個(gè)開模過程 1 第一章 制件的結(jié)構(gòu)與工藝性分析 1 1 制件相關(guān)信息 名稱 耳機(jī) 材料 PBT 精度 一般 零件如圖 1 1 所示 圖 1 1 制件圖 用途 利用 PHT 的特點(diǎn) 制造儀器耳機(jī) 一方面防塵 阻擋異物進(jìn)入儀器 另一方面可從頂部區(qū)域 觀察儀器內(nèi)部油面 以便隨時(shí)掌握油量 及時(shí)添加 側(cè) 壁上長條形孔洞 用于扣緊耳機(jī) 保證耳機(jī)與儀器牢固結(jié)合 表面質(zhì)量要求 要求頂面必須光滑平整 無澆口痕跡及頂出痕跡 四壁光滑 無明顯痕跡 1 2 材料的相關(guān)性質(zhì) 1 2 1 基本特性 PS 聚苯乙烯 是無色透明并有金屬光澤的非結(jié)晶型線性結(jié)構(gòu)的高聚物 落 地式發(fā)出類似金屬的聲音 密度為 1 054g cm3 聚苯乙烯的透明度好 透光率高 2 在塑料中期光學(xué)性能僅次于有機(jī)玻璃 聚苯乙烯有優(yōu)良的電性能 尤其是高頻絕 緣性能 并具有一定的化學(xué)穩(wěn)定性 聚苯乙烯能耐除硝酸以外的酸及堿 醇 油 水等 但對與氧化劑 苯 四氯化碳 酮類 酯類等的抵抗力較差 聚苯乙烯的 著色性能優(yōu)良 能染成各種鮮艷的顏色 但其耐熱性低 熱變形溫度一般在 70 90 所以只能用在不高的溫度下 聚苯乙烯質(zhì)地硬而脆 有較高的熱膨脹系數(shù) 塑件易產(chǎn)生內(nèi)應(yīng)力易開裂 因此限制了它在工程上的應(yīng)用 近幾十年來 由于有 了改性聚苯乙烯和以聚苯乙烯為基體的共聚物 從而擴(kuò)大了它的用途 1 2 2 主要用途 聚苯乙烯是僅次于聚乙烯和聚氯乙烯的第三大塑料品種 在工業(yè)上可用作制 作儀表外殼 燈罩 化學(xué)儀器零件 透明模型等 在電器方面用于制作良好的絕 緣材料 如電視機(jī)的結(jié)構(gòu)零件 接線盒和電池盒等 在日用品方面則廣泛用于制 作包裝材料 各種容器和玩具等 1 2 3 成型特點(diǎn) 聚苯乙烯成型性能優(yōu)良 吸水性小 可不進(jìn)行干燥處理 由于熱膨脹系數(shù)較 高 故而塑件中不宜含有嵌件 否則會(huì)因兩者的熱膨脹系數(shù)相差太大而導(dǎo)致開裂 宜采用高料溫 高模具溫度 低注射壓力成型并延長注射時(shí)間 以防止縮孔和變 形 降低內(nèi)應(yīng)力 由于聚苯乙烯流動(dòng)性很好 故而在模具設(shè)計(jì)中大多采用點(diǎn)澆口 進(jìn)料 聚苯乙烯可采用注射 擠出 真空等多種方法成型 1 3 塑件的脫模斜度 由于塑件成型冷卻過程中產(chǎn)生收縮 使其緊箍在凸?；蛐托旧?為了便于脫 模 防止因脫模力過大而拉壞塑件或使其表面受損 與脫模方向平行的塑件內(nèi) 外表面都應(yīng)具有合理的斜度 以下是 PS 的脫模斜度推薦值 型腔 35 1 30 型芯 30 40 對于本制件而言 型腔取 1 脫模斜度 型芯取 30 脫模斜度 3 1 4 塑件的尺寸精度及表面質(zhì)量要求 該制件為簡單的殼類零件 側(cè)面有一成型孔 表面粗糙度為 0 6 屬于一般的 粗糙度要求 由于上表面要求不能出現(xiàn)任何形式的不光整現(xiàn)象 側(cè)面也要求盡量平整 故 而最初大致確定 制件注塑成型時(shí) 從底部耳邊處進(jìn)料 即澆口開在耳邊 同時(shí) 剛好開在最大分型面處 制件各個(gè)尺寸的相關(guān)要求如下 制件內(nèi)輪廓徑向尺寸 44 和側(cè)壁成型孔尺寸 18 4 為 MT3 其余尺寸 為一 般精度 MT5 4 第二章 初選注射機(jī) 2 1 計(jì)算塑件體積和最大投影面積 考慮到制件形狀簡單 體積較小 批量不大 故而初定模具生產(chǎn)為一模兩腔 一次開模 耗費(fèi)塑料的總體積 可以分兩部分 制件部分的體積 V1 和料把的體 積 V2 V1KPCA 248 1kN 公式 5 2 故注塑機(jī)的額定鎖模力符合要求 5 4 模具安裝尺寸的校核 5 41 噴嘴尺寸校核 注塑模澆口套始端凹坑的球面半 R2 應(yīng)大于注塑機(jī)噴嘴球頭半徑 R1 以利用同 心和緊密接觸 本設(shè)計(jì)按半徑 R2 R1 0 5 2 計(jì)算 故符合要求 主流道的始 端直徑 d1 應(yīng)大于注塑機(jī)噴嘴孔直徑 d2 本設(shè)計(jì)按 d1 d2 0 5 1 mm 關(guān)系計(jì)算 亦符合要求 5 4 2 模具厚度校核 模具厚度 閉合高度 必須滿足下式 maxminH 式中 所設(shè)計(jì)的模具高度 mm H 注塑機(jī)所允許的最小模具厚度 mm in 注塑機(jī)所允許的最大模具厚度 mm max 結(jié)合注塑機(jī)的參數(shù) 模具總高度為 235mm XS Z125 型號注射機(jī)的裝模高度介 于 200mm 與 300mm 之間 因此本設(shè)計(jì)符合要求 5 5 開模行程的校核 27 注塑機(jī)模座間距是指注塑機(jī)動(dòng)模座和定模座之間的間距 對于所選用的注塑 機(jī) 模具的閉模高度必須滿足 maxminH 開模取出塑件所需的開模距離必須小于注塑機(jī)的最大開模行程 本設(shè)計(jì)選用 注塑機(jī)為液壓 機(jī)械式鎖模機(jī)構(gòu) 液壓 機(jī)械式鎖模機(jī)構(gòu)的最大開模行程由屈肘機(jī) 構(gòu)的最大行程決定 與模具厚度決定無關(guān) 本設(shè)計(jì)為單分型面注塑模具 其開模行程按下式校核 m105H21 S 式中 S 注塑機(jī)最大開模行程 移動(dòng)模板臺(tái)面行程 mm 塑件的脫模距離 mm 1 包括流道凝料在內(nèi)的塑件高度 mm 2 本設(shè)計(jì)中 為 24mm 為 88mm 選用的注塑機(jī)的開程12 行程 S 為 325mm 代入式中 易知符合上式 28 結(jié) 論 本次設(shè)計(jì)前后經(jīng)歷了 10 周 由于之前所學(xué)的課程 塑料成型工藝與模具設(shè) 計(jì) 和在模具拆裝實(shí)驗(yàn)室對于模具的內(nèi)部結(jié)構(gòu)及其工作原理都有了一定的了解 因此也為本設(shè)計(jì)打下了基礎(chǔ) 本次設(shè)計(jì)中我查閱了大量的文獻(xiàn) 資料 搜集了很 多有關(guān)模具設(shè)計(jì)的信息和例子 從中不但將以前學(xué)過的有關(guān)模具的知識加以回顧 和進(jìn)一步理解 而且還將模具設(shè)計(jì)的有關(guān)知識系統(tǒng)化 對于我所作課題塑料蓋注塑模模具設(shè)計(jì) 在選用設(shè)計(jì)方案時(shí) 我比較了多種 方案 在本次設(shè)計(jì)中 我也遇到了很多困難 特別是在制圖過程中出現(xiàn)了很多錯(cuò) 誤 最后在老師和同學(xué)們的幫助下都得到了解決 總之 經(jīng)過本次設(shè)計(jì)我學(xué)到了 很多知識 懂得了在面對實(shí)際問題如何解決問題 并對以前的學(xué)過的知識有了比 較系統(tǒng)的復(fù)習(xí) 尤其是 機(jī)械制圖 公差與檢測 和 塑料成型工藝與模具設(shè) 計(jì) 這幾門課 29 謝 辭 時(shí)間過得真快 轉(zhuǎn)眼間大學(xué)生活已經(jīng)漸進(jìn)尾聲 在這次畢業(yè)設(shè)計(jì)里我學(xué)到了 很多東西 可謂受益匪淺 首先 畢業(yè)設(shè)計(jì)鞏固了我三年來所學(xué)的知識 由于時(shí)間的緣故 造成了我對 以前所學(xué)知識的遺忘和生疏 而這次的畢業(yè)設(shè)計(jì) 讓我進(jìn)一步復(fù)習(xí)了課本 是對 所學(xué)知識的一次溫習(xí) 也是一次重新的學(xué)習(xí) 從而達(dá)到了鞏固學(xué)習(xí)的目的 其次 這次畢業(yè)設(shè)計(jì)提高了我發(fā)現(xiàn)問題 分析問題和解決問題的能力 由于 此次設(shè)計(jì)的規(guī)模超過了以往的任何一次課程設(shè)計(jì) 所以這次畢業(yè)設(shè)計(jì)是對我們綜 合能力的一次考驗(yàn) 這次設(shè)計(jì)大大提高了我們動(dòng)手操作能力 邏輯思維能力等等 這次設(shè)計(jì)加深了我對模具知識的了解 對模具的四大系統(tǒng)及開合模過程都有了更 深的認(rèn)識 由于時(shí)間的緣故和自己模具知識的不足 在我的畢業(yè)設(shè)計(jì)中會(huì)有很多不恰當(dāng) 的地方 請各位老師多多指教 多提寶貴意見 首先感謝學(xué)校及學(xué)院各位領(lǐng)導(dǎo)的悉心關(guān)懷和耐心指導(dǎo) 特別要感謝沈俊芳老 師給我的指導(dǎo) 在設(shè)計(jì)和說明書的寫作過程中 我得到沈老師的細(xì)心教導(dǎo)和認(rèn)真 指點(diǎn) 使我的理論知識和動(dòng)手操作能力都有了很大的提高與進(jìn)步 對模具設(shè)計(jì)與 制造的整個(gè)工藝流程也有了一個(gè)基本的掌握 在他身上 時(shí)刻體現(xiàn)著作為科研工 作者所特有的嚴(yán)謹(jǐn)求實(shí)的教學(xué)風(fēng)范 勇于探索的工作態(tài)度和求同思變 不斷創(chuàng)新 的治學(xué)理念 他不知疲倦的敬業(yè)精神和精益求精的治學(xué)要求 端正了我的學(xué)習(xí)態(tài) 度 使我受益匪淺 另外 還要感謝和我同組的其他同學(xué) 他們在尋找資料 解答疑惑 實(shí)驗(yàn)操 作 論文修改等方面 都給了我很大幫助和借鑒 最后 感謝所有給予我關(guān)心和支持的老師和同學(xué)使我能如期完成這次畢業(yè)設(shè) 計(jì) 感謝各位老師和同學(xué) 感謝學(xué)校這三年對我的培養(yǎng)和教導(dǎo) 感謝各位領(lǐng)導(dǎo)各位老師的諄諄教導(dǎo) 參考文獻(xiàn) 1 陳于萍 周兆元 互換性與測量技術(shù)基礎(chǔ) 第二版 北京 機(jī)械工業(yè)出版 30 社 2005 2 劉小年 陳婷 機(jī)械制圖 第三版 北京 機(jī)械工業(yè)出版社 2006 3 許德珠 機(jī)械工程材料 第二版 北京 高等教育出版社 2001 4 屈華昌 塑料成型工藝與模具設(shè)計(jì) 第二版 北京 高等教育 出版社 2007 5 黃毅宏 李明輝 模具制造技術(shù) 北京 高等教育出版社 2002 6 楊成美 模具專業(yè)英語 大連 大連理工大學(xué)出版社 2007 7 梁俊有 CAD 工程設(shè)計(jì) 呼和浩特 遠(yuǎn)方出版社 2005 8 許發(fā)樾 實(shí)用模具設(shè)計(jì)與制造手冊 北京 機(jī)械工業(yè)出版社 2000 9 王孝培 塑料成型工藝及模具簡明手冊 北京 機(jī)械工業(yè)出版社 2004 10 北京科技大學(xué) 東北大學(xué) 工程力學(xué) 北京 高等教育出版社 1997 11 許洪斌 樊澤興 塑料注射成型工藝及模具 北京 化學(xué)工業(yè)出版社 2006 12 閻亞林 塑料模具圖冊 北京 高等教育出版社 2004 13 劉昌祺 塑料模具設(shè)計(jì) 北京 機(jī)械工業(yè)出版社 1998 14 陳世煌 陳可娟 塑料注射成型模具設(shè)計(jì) 北京 國防工業(yè)出版社 2004 15 程燕軍 柳舟通 沖壓與塑料成型設(shè)備 北京 科學(xué)出版社 2006 16 楊占堯 注塑模具典型結(jié)構(gòu)圖例 北京 化學(xué)工業(yè)出版社 2000 畢業(yè)設(shè)計(jì) 論文 中期報(bào)告 題目 耳機(jī)外殼塑料模具設(shè)計(jì) 系 別 機(jī)電信息系 專 業(yè) 機(jī)械設(shè)計(jì)制造及其自動(dòng)化 班 級 姓 名 學(xué) 號 導(dǎo) 師 2013 年 3 月 25 日 1 設(shè)計(jì) 論文 進(jìn)展?fàn)顩r 1 分析零件的成形工藝性 通過查閱書籍資料及查閱網(wǎng)絡(luò)數(shù)據(jù) 發(fā)現(xiàn)聚乙烯塑料重量輕 物理性能 化學(xué)性 能及電氣性能等均很優(yōu)良 且很容易成型 價(jià)格便宜 所以 最終確定所制作塑 件材料為低壓聚乙烯 并根據(jù)實(shí)體塑件測量出實(shí)際尺寸 2 澆注系統(tǒng)的選擇 根據(jù)所選塑料的工藝性及塑件的形狀 決定選取點(diǎn)澆法澆注 所選澆口類型 為側(cè)澆口 3 分型面的選擇 選擇塑件截面最大的部位 4 澆注系統(tǒng)的設(shè)計(jì)與選擇 包括主流道 分流道 澆注口的設(shè)計(jì)與選擇 5 繪制完成了塑件的 CAD 二維圖和 Proe 三維圖 繪制模具裝配圖草圖 6 設(shè)計(jì)的耳機(jī)塑件圖見 圖 1 二維零件圖 圖 2 三維零件圖 7 方案確定 1 課題名稱 耳機(jī)模具設(shè)計(jì) 2 材料選擇 聚乙烯 3 生產(chǎn)批量 大 4 精度要求 中 5 塑料等級 6 級 6 方案確定 該產(chǎn)品為大批量生產(chǎn) 故設(shè)計(jì)的模具要有較高的注塑效率 澆 注系統(tǒng)要能自動(dòng)脫模 可采用點(diǎn)澆口自動(dòng)脫模結(jié)構(gòu) 由于該塑件要求批量大 制件 較小 為取得較大的經(jīng)濟(jì)效益 所以模具采用一模四腔結(jié)構(gòu) 此方案生產(chǎn)效率高 操作簡便 動(dòng)作可靠 方便脫出流道凝料 經(jīng)濟(jì)性價(jià)比高 故選此次模具設(shè)計(jì)選用 方案 模具設(shè)計(jì)圖見圖 3 圖 3 裝配圖 2 存在問題及解決措施 在本次設(shè)計(jì)階段內(nèi) 我深刻的體會(huì)到自己所儲(chǔ)備的知識的不足 以及所查閱 資料的缺乏和片面性 尤其針對于注塑機(jī)的選型過程 大部分的資料里面都只有 注塑機(jī)的型號和具體性能數(shù)據(jù) 但是卻缺少如何選擇與校核的方法 令人百思不 得其解 最后 本著求同存異的想法 綜合多處查詢資料的結(jié)果 選擇基礎(chǔ)結(jié)構(gòu) 進(jìn)行設(shè)計(jì) 我也應(yīng)該加強(qiáng)自己對塑料模具知識的學(xué)習(xí) 努力使自己所設(shè)計(jì)出來的模具更 具備可行性和實(shí)用性 同時(shí) 也應(yīng)該加強(qiáng)自己與老師 與同學(xué)之間的溝通 使自 己的設(shè)計(jì)在互相印證中得到提高和完善 加深自己對本次設(shè)計(jì)的理解 最后 我相信自己可以保持積極樂觀的態(tài)度去繼續(xù)接下來的設(shè)計(jì)過程 在老 師的悉心教導(dǎo)下 能夠快速 有效的完成所有設(shè)計(jì)流程 并最終順利結(jié)束本次畢 業(yè)設(shè)計(jì) 3 后期工作安排 1 接下來將用兩周左右的時(shí)間對成型零件的設(shè)計(jì)計(jì)算徹底完成 2 用兩周時(shí)間繪制模具各主要零部件的零件圖及總體裝配圖 3 用兩周時(shí)間用 Proe 繪圖軟件對主要零部件進(jìn)行三維建模 繪制出爆炸圖 4 用兩周時(shí)間整理相關(guān)資料 撰寫畢業(yè)論文 準(zhǔn)備畢業(yè)答辯 指導(dǎo)教師簽字 年 月 日 Int J Adv Manuf Technol 2001 17 297 304 2001 Springer Verlag London Limited Optimum Gate Design of FreeForm Injection Mould using the Abductive Network J C Lin Department of Mechanical Design Engineering National Hu Wei Institute of Technology Yunlin Taiwan This study uses the injection position and size of the gate as the major control parameters for a simulated injection mould Once the injection parameters gate size and gate position are given the product performance deformation can be accurately predicted by the abductive network developed To avoid the numerous influencing factors first the part line of the parameter equation is created by an abductive network to limit the range of the gate The optimal injection parameters can be searched for by a simulation annealing SA optimisa tion algorithm with a performance index to obtain a perfect part The major purpose is searching for the optimal gate location on the part surface and minimising the air trap and deformation after part formation This study also uses a prac tical example which has been and proved by experiment to achieve a satisfactory result Keywords Abductive network Injection mould Simulation annealing SA 1 Introduction Owing to the rapid development of industry and commerce in recent years there is a need for rapid and high volume production of goods The products are manufactured using moulds in order to save the time and cost Plastic products are the majority Owing to these products not requiring complicated processes it is possible to cope with market demand speedily and conveniently In traditional plastic production the designs of the portions of the mould are determined by humans However because of the increased performance requirements the complexity of plastic products has increased First the geometric shapes of the plastic products are difficult to draw and the internal shape is often complex which also affects the production of the product Injection processing can be divided into three stages Correspondence and offprint requests to Dr J C Lin Department of Mechanical Design Engineering National Hu Wei Institute of Technology Yunlin 632 Taiwan E mail linrcKsunws nhit edu tw 1 Heat the plastic material to a molten state Then by high pressure force the material to the runner and then into the mould cavity 2 When the filling of the mould cavity is completed more molten plastic should be delivered into the cavity at high pressure to compensate for the shrinkage of the plastic This ensures complete filling of the mould cavity 3 Take out the product after cooling Though the filling process is only a small proportion of the complete formation cycle it is very important If filling in incomplete there is no pressure holding and cooling is required Thus the flow of the plastic fluid should be controlled thoroughly to ensure the quality of the product The isothermal filling model of a Newtonian fluid is the simplest injection mould flow filling model Richardson 1 produced a complete and detailed concept The major concept is based on the application of lubrication theory and he simplified the complex 3D flow theory to 2D Hele Shaw flow The Hele Shaw flow was used to simulate the potential flow and was furthermore used in the plasticity flow of the plastic He assumed the plasticity flow on an extremely thin plate and fully developed the flow by ignoring the speed change through the thickness Kamal et al used similar methods to obtain the filling condition for a rectangular mould cavity and the analyti cal result obtained was almost identical to the experimental result Plastic material follows the Newtonian fluid model for flow in a mould cavity and Bird et al 2 4 derived mould flow theory based on this When the shape of a mould is complicated and there is variation in thickness then the equilibrium equa tions changes to nonlinear and has no analytical solution Thus it can be solved only by finite difference or numerical solutions 2 5 Of course as the polymer is a visco elastic fluid it is best to solve the flow problem by using visco elasticity equations In 1998 Goyal et al used the White Metzner visco elasticity model to simulate the disk mould flow model for central pouring Metzner using a finite difference method to solve the governing equation fould the visco elasticity effect would not change the distribution of speed and temperature However it affects the stress field very much If it is a pure visco elastic 298 J C Lin flow model the popular GNF model is generally used to perform numerical simulation Currently finite element methods are mostly used for the solution of mould flow problems Other methods are pure visco elastic models such as C FOLW and MOLD FLOW software We used this method as well Some software employs the visco elastic White Metzner model but it is limited to 2D mould flow analysis Simple mould flow analysis is limited by CPU time For the complicated mould shapes Papthanasion et al used UCM fluid for filling analysis using a finite difference method and BFCC coordination system application for the solution of the more complicated mould shape and filling problem but it was not commercialised 6 Many factors affect plastic material injection The filling speed injection pressure and molten temperature holding press ure 7 12 cooling tube 13 14 and injection gate affect the accuracy of the plastic product because when the injection processing is completed the flow of material in the mould cavity results in uneven temperature and pressure and induces residual stress and deformation of the workpiece after cooling It is difficult to decide on the mould part surface and gate positions Generally the mould part surface is located at the widest plane of the mould Searching for the optimal gate position depends on experience Minimal modification to the mould is required if you are lucky However the time and cost required for the modification of most injection moulds exceeds the original cost if the choice of the part line is poor For the mould part surface many workers used various methods to search for the optimal mould part line such as geometric shape and feature based design 15 17 Some workers used finite element methods and abductive networks to look for the optimal gate design for a die casting mould 18 This study used an abductive network to establish the para meter relationship of the mould part line and used this formula for searching for 22 points on the injection mould part line to serve as the location for an injection gate Abductive networks are used to match injection pressure and pressure holding time to perform injection formation analysis and to establish a relationship between these parameters and the output result of the injection process It has been shown that prediction accuracy in abductive networks is much higher than that in other networks 19 Abductive networks based on the abductive modelling tech nique are able to represent complex and uncertain relationships between mould flow analysis results and injection parameters It has beeen shown that the injection strain and injection stress in a product can be predicted with reasonable accuracy based on the developed networks The abductive network has been constructed once the relationships of gate location that are input and simulated have been determined an appropriate optimisation algorithm with a performance index is then used to search for the optimal location parameters In this paper an optimisation method for simulated annealing 20 is presented The simulated annealing algorithm is a simulation of the annealing process for minimising the perform ance index It has been successfully applied to filtering in image processing 21 VLSI layout generation 22 discrete tolerance design 23 wire electrical discharge machining 24 deep draw clearance 25 and casting die runner design 26 etc It provides an experimental foundation based on theory for the development and application of the technologies 2 Mould Flow Theory The mould flow analysis include four major parts 1 Filling stage 2 Pressure holding stage 3 Cooling and solidification stage 4 Shrinkage and warp i e stress residue stage Thus the major mould flow equations are divided into four groups In the filling stage the mould cavity is filled with molten plastic fluid at high presssure Thus the governing equations include 1 Continuity equation The plastic deformation or shape change accompany the flow during the filling process mass conservation r t V 0 1 r plastic density V vector velocity 2 Momentum equation Newton s second law is used to derive the momentum acceleration condition or force balance generated by plastic flow r F V t V V G VP t rf 2 P flow pressure f body force t stress tensor 3 Energy equation The energy conservation of system and laws of conservation of flow material if the fluid is incom pressible rC P F T t V T G q t V 3 T temperature C P specific heat of constant pressure q heat flux 4 Rheology equation t f n g T P 4 g V V T 5 V deform tensor V T transport vector Holding pressure analysis The holding pressure process is to maintain the pressure after the mould cavity is filled in order to inject more plastic to compensate for the shrinkage in cooling r V 1 t P x 1 F t 11 x 1 t 21 x 2 t 31 x 3 G 6 r V 2 t P x 2 F t 12 x 1 t 22 x 2 t 32 x 3 G 7 r V 3 t P x 1 F t 13 x 1 t 23 x 2 t 33 x 3 G 8 Optimum Gate Design of FreeForm Injection Mould 299 Cooling analysis The analysis of the cooling process con siders the relationship of the plastic flow distribution and heat transmission The homogenous mould temperature and the sequence of filling will be affected by the shrinkage of the product formed If the temperature is distributed non uniformly it tends to produce warp This is mainly due to heat transfer and crystallisation heat of the plastic rC P T t k F 2 T x 2 1 2 T x 2 2 2 T x 3 3 G rC P rDH 9 r crystallisation rate DH crystallisation heat 3 Abductive Network Synthesis and Evaluation Miller 22 observed that human behaviour limits the amount of information considered at a time The input data are summar ised and then the summarised information is passed to a higher reasoning level In an abductive network a complex system can be decom posed into smaller simpler subsystems grouped into several layers using polynomial function nodes These nodes evaluate the limited number of inputs by a polynomial function and generate an output to serve as an input to subsequent nodes of the next layer These polynomial functional nodes are specified as follows 1 Normaliser A normaliser transforms the original input variables into a relatively common region a 1 q 0 q 1 x 1 10 Where a 1 is the normalised input q 0 q 1 are the coefficients of the normaliser and x 1 is the original input 2 White node A white node consists of linear weighted sums of all the outputs of the previous layer b 1 r 0 r 1 y 1 r 2 y 2 r 3 y 3 r n y n 11 Where y 1 y 2 y 3 y n are the input of the previous layer b 1 is the output of the node and the r 0 r 1 r 2 r 3 r n are the coefficients of the triple node 3 Single double and triple nodes These names are based on the number of input variables The algebraic form of each of these nodes is shown in the following single c 1 s 0 s 1 z 1 s 2 z 2 1 s 3 z 3 1 12 double d 1 t 0 t 1 n 1 t 2 n 2 1 t 3 n 3 1 t 4 n 2 t 5 n 2 2 t 6 n 3 2 t 7 n 1 n 2 13 triple e 1 u 0 u 1 o 1 u 2 o 2 1 u 3 o 3 1 u 4 o 2 u 5 o 2 2 u 6 o 3 2 u 7 o 3 u 8 o 2 3 u 9 o 3 3 u 10 o 1 o 2 u 11 o 2 o 3 u 12 o 1 o 3 u 13 o 1 o 2 o 3 14 where z 1 z 2 z 3 z n n 1 n 2 n 3 n n o 1 o 2 o 3 o n are the input of the previous layer c 1 d 1 and e 1 are the output of the node and the s 0 s 1 s 2 s 3 s n t 0 s 1 t 2 t 3 t n u 0 u 1 u 2 u 3 u n are the coefficients of the single double and triple nodes These nodes are third degree polynomial Eq and doubles and triples have cross terms allowing interaction among the node input variables 4 Unitiser On the other hand a unitiser converts the output to a real output f 1 v 0 v 1 i 1 15 Where i 1 is the output of the network f 1 is the real output and v 0 and v 1 are the coefficients of the unitiser 4 Part Surface Model This study uses an actual industrial product as a sample Fig 1 The mould part surface is located at the maximum projection area As shown in Fig 1 the bottom is the widest plane and is chosen as the mould part surface However most important is the searching of gate position on the part surface This study establishes the parameter equation by using an abductive neuron network in order to establish the simulated annealing method SA to find the optimal gate path position The parameter equation of a part surface is expressed by F Y X First use a CMM system to measure the XYZ coordinate values in this study z 0 of 22 points on the mould part line on the mould part surface as illustrated in Table 1 and the gate position is completely on the curve in this space Prior to developing a space curve model a database has to be trained and a good relationship msut exist between the control point and abductive network system A correct and Fig 1 Injection mould product 300 J C Lin Table 1 X Y coordinate Set number X coordinate Y coordinate 1 0 02 4 6 2 1 63 4 33 3 3 28 3 5 4 5 29 2 04 5 7 31 0 56 6 9 34 0 9 7 11 33 2 35 8 12 98 3 94 9 13 85 5 57 10 14 12 7 34 11 13 69 9 67 12 12 96 11 9 13 10 00 21 03 14 9 33 23 16 15 8 64 25 28 16 7 98 27 39 17 7 87 28 31 18 7 80 29 29 19 7 83 30 34 20 7 60 31 30 21 7 07 32 15 22 6 11 32 49 precise curve Eq is helpful for finding the optimal gate location To build a complete abductive network the first requirement is to train the database The information given by the input and output parameters must be sufficient A predicted square error PSE criterion is then used to determine automatically an optimal structure 23 The PSE criterion is used to select the least complex but still accurate network The PSE is composed of two terms PSE FSE K P 16 Where FSE is the average square error of the network for fitting the training data and K P is the complex penalty of the network shown by the following equation K P CPM 2s 2 p K N 17 Where CPM is the complex penalty multiplier K P is a coef ficient of the network N is the number of training data to be used and s 2 p is a prior estimate of the model error variance Based on the development of the database and the prediction of the accuracy of the part surface a three layer abductive network which comprised design factors input various Y coordinate and output factors X coordinate is synthesised automatically It is capable of predicting accurately the space curve at any point under various control parameters All poly nomial equations used in this network are listed in Appendix A PSE 5 8 10 3 Table 2 compares the error predicted by the abductive model and CMM measurement data The measurement daa is excluded from the 22 sets of CMM measurement data for establishing the model This set of data is used to test the appropriateness of the model established above We can see from Table 2 that the error is approximately 2 13 which shows that the model is suitable for this space curve Table 2 CMMS coordinate and neural network predict compared it is not included in any original 22 sets database Items CMMS neural network Error values coordinate predict CMMS predict coordinate CMMS Coordinate 11 25 16 0 11 01 16 0 2 13 5 Create the Injection Mould Model Similarly the relationship is established between input para meters gate location and gate size and the output parameter deformation during the injection process To build a complete abductive network the first requirement is to train the database The information given by the input and the output data must be sufficient Thus the training factor gate location for abductive network training should be satisfactory for making defect free products Figure 2 shows the simulation of FEM mould flow Table 3 shows the position of the gate and the maximum deformation of the product obtained from mould flow analysis Based on the development of the injection mould model three layer abductive networks which are comprised of injec tion mould conditions and the injection results deformation are synthesised automatically They are capable of predicting accurately the product strain the result of injection moulded product under various control parameters All polynomial equations used in this network are listed in Appendix B PSE 2 3 10 5 Table 4 compares the error predicted by the abductive model and the simulation case The simulation case is excluded from the 22 sets of simulation cases for establishing the model This set of data is used to test the appropriateness of the model established above We can see from Table 4 that the error is Fig 2 The deformation of FEM mould flow Optimum Gate Design of FreeForm Injection Mould 301 Table 3 Gate location and the maximum strain relationship Set number X coordinate Y coordinate Gate width Gate length Produce max strain 1 0 02 4 6 0 525 1 1475 0 348 2 1 63 4 33 0 7 1 53 0 3153 3 3 28 3 5 0 875 1 9125 0 2710 4 5 29 2 04 1 05 2 295 0 2858 5 7 31 0 56 0 525 1 1475 0 3017 6 9 34 0 9 0 7 1 53 0 526 7 11 33 2 35 0 875 1 9125 0 2369 8 12 98 3 94 1 05 2 295 0 2517 9 13 85 5 57 0 525 1 1475 0 2788 10 14 12 7 34 0 7 1 53 0 2773 11 13 69 9 67 0 875 1 9125 0 2988 12 12 96 11 9 1 05 2 295 0 2997 13 10 00 21 03 0 525 1 1475 0 2576 14 9 33 23 16 0 7 1 53 0 2624 15 8 64 25 28 0 875 1 9125 0 2542 16 7 98 27 39 1 05 2 295 0 2495 17 7 87 28 31 0 525 1 1475 0 2503 18 7 80 29 29 0 7 1 53 0 2456 19 7 83 30 34 0 875 1 9125 0 2596 20 7 60 31 30 1 05 2 295 0 2457 21 7 07 32 15 0 525 1 1475 0 2499 22 6 11 32 49 0 7 1 53 0 2511 Table 4 Mould flow simulated and neural network predict compared it is not included in any original 22 set database Items FEM mould flow Neural network simulation predict X coordinate 11 01 11 01 Y coordinate 16 0 16 0 Gate width 1 8 1 8 Gate height 0 9 0 9 Produce max deformation 0 3178 0 3325 Error values 4 62 FEM predict FEM approximately 4 62 which shows that the model is suitable for this model requirement 6 Simulation Annealing Theory In 1983 a theory that was capable of solving the global optimisation problem was developed for the optimised problem The concept was a powerful optimisation algorithm based on the annealing of a solid which solved the combinatorial optimisation problem of multiple variables When the tempera ture is T and energy E the thermal equilibrium of the system is a Boltzman distribution P r 1 Z T exp S E K B T D 18 Z T normalisation factor K B Boltzman constant Exp E K B T Boltzman factor Metropolis 24 proposed a criterion for simulating the cool ing of a solid to a new state of energy balance The basic criterion used by Metropolis is an optimisation algorithm called simulated annealing The algorithm was developed by Kirk patrick et al 20 In this paper the simulation annealing algorithm is used to search for the optimal control parameters for gate location Figure 3 shows the flowchart of the simulated annealing search First the algorithm is given an initial temperature T s and a final temperature T e and a set of initial process vectors O x The objective function obj is defined based on the injection parameter performance index The objective function can be recalculated for all the different perturbed compensation para meters If the new objective function becomes smaller the peturbed process parameters are accepted as the new process parameters and the temperature drops a little in scale That is T i 1 T i C T 19 where i is the index for the temperature decrement and the C T is the decay ratio for the temperature C T 1 However if the objective function becomes larger the prob ability of acceptance of the perturbed process parameters is given as P r obj exp F Dobj K B T G 20 Where K B is the Boltzman constant and Dobj is the different in the objective function The procedure is repeated until the temperature T i approaches zero It shows the energy dropping to the lowest state Once the