購(gòu)買(mǎi)設(shè)計(jì)請(qǐng)充值后下載，，資源目錄下的文件所見(jiàn)即所得，都可以點(diǎn)開(kāi)預(yù)覽，，資料完整，充值下載可得到資源目錄里的所有文件。。。【注】：dwg后綴為CAD圖紙，doc,docx為WORD文檔，原稿無(wú)水印，可編輯。。。具體請(qǐng)見(jiàn)文件預(yù)覽，有不明白之處，可咨詢QQ:12401814
浙江工貿(mào)職業(yè)技術(shù)學(xué)院汽車與機(jī)電工程系
畢業(yè)設(shè)計(jì)（論文）開(kāi)題報(bào)告
?
課題名稱： 放大鏡模具的設(shè)計(jì)與制造
專 業(yè)：
班 級(jí)：
姓 名：
學(xué) 號(hào)：
指導(dǎo)教師：
2006年 3 月 12日
浙江工貿(mào)職業(yè)技術(shù)學(xué)院汽車與機(jī)電工程系
畢業(yè)設(shè)計(jì)開(kāi)題報(bào)告
1、課題研究的現(xiàn)狀和意義
? 放大鏡做為觀察物體的目視光學(xué)器件，利用光的折射原理可以放大或縮小我們眼中看到的虛象。在市場(chǎng)以及我們生活中應(yīng)用也比較廣泛，分類如下：
?一.按形式
按形式可分為手持放大鏡、發(fā)夾式放大鏡、臺(tái)式放大鏡、落地式放大鏡、筆式放大鏡、小型放大鏡、夾臺(tái)式放大鏡等
二.按領(lǐng)域
? 1.用于軍事的：軍事望遠(yuǎn)鏡 2.用于醫(yī)院的：手術(shù)放大鏡
?3.用于工廠的：刻度放大鏡 4.用于化學(xué)的：化學(xué)顯微鏡
三.按材料
放大鏡的普遍材料是玻璃、塑料做主件。
? 在我們生活中的應(yīng)用的眼鏡、幻燈機(jī)、望遠(yuǎn)鏡、照相機(jī)等等都是來(lái)源于“放大鏡”，以及我們?nèi)松砩系难劬κ侵粡?fù)雜的“放大鏡”。
我們離不開(kāi)“放大鏡”，更需要“放大鏡”為我們的過(guò)去、現(xiàn)在、未來(lái)畫(huà)那宇宙中無(wú)法畫(huà)完整的句號(hào)。
? 本次設(shè)計(jì)的放大鏡是用塑料基于注射模，得到一個(gè)便于隨身攜帶手持的普通放大鏡。
?
?2、課題要解決的問(wèn)題或研究的基本內(nèi)容
? 對(duì)于隨身攜帶的手持放大鏡，用的人并不是廣泛，所以設(shè)計(jì)它在審美觀讓人看了想買(mǎi)是比較重要的；市場(chǎng)上放大鏡對(duì)于透光需求也較高，所以選的材料成本較高，在市場(chǎng)上價(jià)格也較高；還有我設(shè)計(jì)的放大鏡外型尺寸要求也并不要好高，是個(gè)整體不要與其他零件相配。我這次設(shè)計(jì)要解決的問(wèn)題如下：
一：對(duì)放大鏡材料要有透光性 收縮率要求不高
二：設(shè)計(jì)的產(chǎn)品是大批量生產(chǎn)，設(shè)計(jì)的模具要有較高的注塑效率
三：外型設(shè)計(jì)中對(duì)柄的設(shè)計(jì)要讓人有舒適感
四：設(shè)計(jì)的成本及結(jié)構(gòu)要求要盡可能的低
研究的基本內(nèi)容：由于我這次設(shè)計(jì)的放大鏡對(duì)尺寸沒(méi)精度要求，無(wú)須與其他零件相配，所以對(duì)凸凹模零件型腔尺寸可直接按產(chǎn)品尺寸加工。
3、課題研究擬采用的手段和工作路線
用PRO-E三維軟件畫(huà)出產(chǎn)品；在運(yùn)用CAD二維軟件畫(huà)出放大鏡模具的裝配圖，拆畫(huà)所有零件圖，完成畢業(yè)設(shè)計(jì)說(shuō)明書(shū)。
4、課題研究進(jìn)程計(jì)劃
? 第3、4周：了解產(chǎn)品應(yīng)用市場(chǎng)要緊及情況，寫(xiě)開(kāi)題報(bào)告
? 第5．6周：對(duì)產(chǎn)品進(jìn)行認(rèn)識(shí)，從初步到深刻，在到了解
進(jìn)行分析計(jì)算測(cè)量，對(duì)定，動(dòng)模架等進(jìn)行初步設(shè)定
第7.8周：設(shè)計(jì)模具，并繪制部分結(jié)構(gòu)零件
繪制未完成的零件及總裝配圖等并繪出CAD，PRO-E圖
第9周：做答辯課件，電子文檔等，為答辯做準(zhǔn)備?
?
?
?
?
?
?
5、課題成果
論文□ 圖紙□ 產(chǎn)品或作品□ 應(yīng)用程序□
其它：
指導(dǎo)教師意見(jiàn)：
指導(dǎo)教師（簽名）：
年 月 日
教研室主任意見(jiàn)：
教研室主任（簽名）：
年 月 日
目錄
前言
第一章 料工藝分析
1.1分析塑料使用材料的種類及工藝特征
1.2分析塑料的結(jié)構(gòu)工藝性
1.3塑件精度確定
1.4 明確塑件批量生產(chǎn)
1.5 根據(jù)塑件的形狀估算其體積和重量
1.6 確定型腔數(shù)
第二章 定模具結(jié)構(gòu)方案
2.1 確定型腔排列
2.2 確定分型面
2.3 脫模原理
2.4 澆注系統(tǒng)形式
2.4.1 主流道設(shè)計(jì)
2.4.2 分流道設(shè)計(jì)
2.4.3、澆口設(shè)計(jì)
2.5冷卻及加熱系統(tǒng)
第三章 模具設(shè)計(jì)的有關(guān)計(jì)算
3.1模具主要零件的有關(guān)尺寸設(shè)計(jì)
3.1.1型腔和型芯計(jì)算
3.2 型腔厚度和底板厚度的確定
3.3確定零件結(jié)構(gòu)及尺寸
3.3.1定模座板設(shè)計(jì)
3.3.2定模型腔固定板設(shè)計(jì)
3.3.3 動(dòng)模型腔固定板設(shè)計(jì)
3.3.4 支撐板設(shè)計(jì)設(shè)計(jì)
3.3.5 推桿固定板設(shè)計(jì)
第四章 初選注射機(jī)
4.1計(jì)算澆注系統(tǒng)體積
4.1初選注射機(jī)
第五章 核注射機(jī)有關(guān)工藝參數(shù)
5.1注射量的校核
5.2鎖模力與注射壓力
5.3模具厚度H與注射機(jī)閉合高度
第六章 結(jié)束語(yǔ)
參考文獻(xiàn)
摘要 注塑模具是在成型中賦予塑料以形狀和尺寸的部件。模具的結(jié)構(gòu)雖然由于塑料品種和性能、塑料制品的形狀和結(jié)構(gòu)以及注射機(jī)的類型等不同而可能千變?nèi)f化，但是基本結(jié)構(gòu)是一致的。模具主要由澆注系統(tǒng)、成型零件和結(jié)構(gòu)零件三部分組成。其中澆注系統(tǒng)和成型零件是與塑料直接接觸部分，并隨塑料和制品而變化，是塑模中最復(fù)雜，變化最大，要求加工光潔度和精度最高的部分。
對(duì)此次放大鏡無(wú)多大要求，它的整體尺寸不大，但要大批生產(chǎn)，為提高生產(chǎn)率，降低成本，故采用模具成批注射生產(chǎn)。并且該產(chǎn)品為放大鏡要透光，所以材料采用聚苯乙烯（PS）做為材料。
對(duì)于澆注系統(tǒng)和成型零件的設(shè)計(jì)；澆注系統(tǒng)是指塑料從射嘴進(jìn)入型腔前的流道部分，包括主流道、冷料穴、分流道和澆口等。成型零件是指構(gòu)成制品形狀的各種零件，包括動(dòng)模、定模和型腔、型芯等。
此套放大鏡模實(shí)現(xiàn)部分機(jī)械操作自動(dòng)化，澆注系統(tǒng)采用普通流道，進(jìn)行一模二腔注射。頂出機(jī)構(gòu)由2條型芯和一條推桿頂出，型腔分動(dòng)模型腔和定模型腔。
前言
此次設(shè)計(jì)為放大鏡的注射成型模具設(shè)計(jì)。對(duì)于這次的設(shè)計(jì)首要制定的塑料成型工藝以及合理設(shè)計(jì)塑料成型模具的過(guò)程。
前面部分主要說(shuō)明塑料成型的必要理論基礎(chǔ)，包括高分子聚合物結(jié)構(gòu)特點(diǎn)與性能，尤其是聚合物的熱力學(xué)性能和化學(xué)性質(zhì)，還有聚合物熔體在成型過(guò)程中的流動(dòng)狀態(tài)及物理和化學(xué)變化。后面部分說(shuō)明的是注射成型模具設(shè)計(jì)的最復(fù)雜也最具代表性的部分，主要說(shuō)明注射成型模具的設(shè)計(jì)，包括澆注系統(tǒng)（主流道，澆口，分流道）、成型零件（型芯，型腔，推桿等）的設(shè)計(jì)，對(duì)所選注射機(jī)的校核等有關(guān)設(shè)計(jì)。
由于塑料注射成型模具對(duì)于實(shí)踐性很強(qiáng)，并且技術(shù)正在飛速發(fā)展中，所以在設(shè)計(jì)過(guò)程中注重理論聯(lián)系實(shí)際，對(duì)于書(shū)中的知識(shí)要加以聯(lián)系實(shí)際，從而使模具設(shè)計(jì)得更加合理。分，包括主流道、冷料穴、分流道和澆口等。成型零件是指構(gòu)成制品形狀的各種零件，包括動(dòng)模、定模和型腔、型芯、成型桿以及排氣口等
第一章 塑件工藝分析
1.1 分析塑件使用材料的種類及工藝特征
該材料為聚苯乙烯（PS），是一種透光性塑料，密度為1.05g/cm*，透光度達(dá)88%—92%，有優(yōu)異在著色性能。制品的穩(wěn)定性非常好，最高連續(xù)使用溫度為60度到80度。具有一般塑料的電絕緣性能和耐化學(xué)腐蝕性能；注塑壓力為60-100Mpa；成型收縮率為0.5-0.8%。
聚苯乙烯的缺點(diǎn)是制品具有較大的脆性，易受沖擊而開(kāi)裂，制品表面受摩擦而易起刮痕。在聚苯乙烯樹(shù)脂中加入橡膠成分可使其耐沖擊性提高5倍-10倍，但會(huì)失去透明特性。
聚苯乙烯塑料廣泛用于家用器皿、玩具、生活和文教用品、家電、輕工儀表的殼體、燈罩、圓珠筆桿等。發(fā)泡型的聚苯乙烯塑料用于防震、隔音材料及電冰箱襯里等。
1.2 分析塑件的的結(jié)構(gòu)工藝性
塑件尺寸不大，結(jié)構(gòu)比較簡(jiǎn)單，對(duì)塑件的尺寸測(cè)量和型芯計(jì)算無(wú)多大影響，其它結(jié) 構(gòu)特征也符合塑件的設(shè)計(jì)要求。
具體尺寸如圖所示：
（圖1-1）(放大鏡零件圖)
1.3 塑件精度確定
因考慮塑件工作要求不高,各尺寸也不大，結(jié)構(gòu)簡(jiǎn)單，故先普通精度:IT4級(jí)
1.4 明確塑件批量生產(chǎn)
該塑件要求批量生產(chǎn)。
1.5 根據(jù)塑件的形狀估算其體積和重量
使用UG或Pro/E軟件畫(huà)出三維實(shí)體圖，軟件能自動(dòng)計(jì)算出所畫(huà)圖形的體積，當(dāng)然也可根據(jù)形狀進(jìn)行手動(dòng)幾何計(jì)算得到圖形的體積。
通過(guò)計(jì)算塑件的體積（計(jì)算過(guò)程從略），
式中：——————為放大鏡中圓柱面的體積
——————為放大鏡中柄的體積
————為整個(gè)放大鏡塑件的總體積
可得塑件的質(zhì)量為：
式中：——塑料密度，（g/cm3） ——塑件質(zhì)量，（g）
1.6 確定型腔數(shù)
該產(chǎn)品需批量生產(chǎn)，設(shè)計(jì)的模具要有較高的注射效率，采用一模二腔的模具結(jié)構(gòu)。
第二章 確定模具結(jié)構(gòu)方案
2.1 確定型腔排列
型腔排列選擇中，由于此次采用的是一模二腔，放大鏡的結(jié)構(gòu)并不是直接圓形或矩形，初步設(shè)定排列方式有二種選擇：
（圖2-1）（型腔的排列的二種方式）
因第一種排列方式的注射效率高，由此模具設(shè)計(jì)選用第一種型腔排列方式。
2．2確定分型面
在模具設(shè)計(jì)中分型面的選擇很重要，它決定了模具的結(jié)構(gòu)，應(yīng)根據(jù)分型面選擇原則和塑件的成型要求來(lái)選擇。
如下圖所示：
（圖2-2）（分型面以及成型位置）
2.3 脫模原理：
此次分型為一次分型，開(kāi)模在分型面(上圖所示)進(jìn)行分模，動(dòng)模型腔板和定模型腔板分開(kāi)，再由推桿固定板推動(dòng)推桿和型腔桿(型芯）頂出塑件和澆流道內(nèi)的塑件。而后塑件自動(dòng)脫落，再人工取出塑件即可。
2.4 澆注系統(tǒng)形式
采用普通澆注系統(tǒng)，由于二型腔模，必須設(shè)置分流道，用點(diǎn)澆口形式從零件內(nèi)部進(jìn)料，利用分型面間隙排氣。
2.4.1 主流道設(shè)計(jì)
在臥式或立式注射機(jī)上使用的模具中，主流道垂直于分型面。為了讓主流道凝料能順利從澆口中拔出，主流道設(shè)計(jì)成圓錐形，其錐角為2－5o，取3o。小端直徑d比注射機(jī)噴嘴直徑大0.5－1mm,取值為5mm，注射機(jī)噴嘴的球面在該位置與模具接觸并且貼合，因此要求主流道球面半徑比噴嘴球面大1－2mm。
2.4.2 分流道設(shè)計(jì)
a．分流道的形狀和尺寸
分流道開(kāi)設(shè)在定模板上，其截面形狀為梯形，有經(jīng)驗(yàn)公式h=2b/3（b為梯形大底邊寬度，mm；h為梯形的高度，mm），可給h=3mm，b=3.5mm，梯形的側(cè)面斜角
=5o－10o，底部以圓角相連。
b、分流道的表面粗糙度
由于分流道與模具接觸的外層塑料迅速冷卻，只有內(nèi)部的熔體流動(dòng)狀態(tài)比較理想，因此分流道表面粗糙度要求不太低，一般Ra取1.6μm左右，這可增加對(duì)外層塑料熔體的阻力，使外層塑料冷卻皮層固定，形成絕熱層
2.4.3、澆口設(shè)計(jì)
澆口套可選標(biāo)準(zhǔn)件，因?yàn)樽⑺軝C(jī)的噴嘴口直徑為4mm，可選取進(jìn)料口直徑為5mm的澆口套。此次采用的是側(cè)澆口中的扇開(kāi)澆口，取在與型腔接合處形成長(zhǎng)L=1mm厚t=0.5mm的進(jìn)料口，進(jìn)料寬度為b=5mm，扇形長(zhǎng)度為3.5mm，塑件熔體通過(guò)它進(jìn)入型腔。
采用扇形澆口，使塑料熔體在寬度方向上的流動(dòng)得到更均勻的分配，塑件的內(nèi)應(yīng)力因之較小，還可避免流紋及定向效應(yīng)所帶來(lái)的不良影響，減少帶入空氣的可能性，但澆口痕跡較明顯。
2.5冷卻及加熱系統(tǒng)
該模具注射成型時(shí)不需要太高要求，因而在模具上可不設(shè)加熱系統(tǒng)。是否需要冷卻系統(tǒng)可作如下計(jì)算
設(shè)定模具平均工作溫度為50℃，用常溫20℃的水作為模具冷卻介質(zhì)，其出口溫度為30℃，產(chǎn)量為（初選每二分鐘一套）
查表聚苯乙烯的單位熱流量為
故冷卻水體積流量：
式中：
—冷卻水體積流量，（）
—單位時(shí)間注射人模具內(nèi)的塑料熔體的質(zhì)量，（）
—單位時(shí)間內(nèi)樹(shù)脂在模具內(nèi)釋放的熱焓量，（，ABS為）
—冷卻水的比熱容，（）
—冷卻水的密度，（）
—冷卻水出口處溫度，（℃）
—冷卻水進(jìn)口處溫度，（℃）
查表可知所需的冷卻水道直徑比較小，所以，選直徑為的冷卻水道一個(gè)型腔一條。
第三章 模具設(shè)計(jì)的有關(guān)計(jì)算
3.1模具主要零件的有關(guān)尺寸設(shè)計(jì)
3.1.1型腔和型芯計(jì)算
列表中成型零件工作尺寸計(jì)算時(shí)都按平均尺寸，平均收縮率，平均制造公差和平均磨損量來(lái)計(jì)算。
由塑料模具設(shè)計(jì)課程設(shè)計(jì)指導(dǎo)書(shū)查表2-5得：
聚苯乙烯（PS）的成型收縮率為0.5-0.8%,故平均收縮率為,考慮到工廠模具制造的條件，模具制造公差一般取
計(jì)算如下表：
類別
尺寸類型
塑件尺寸
計(jì)算公式
型腔或型芯的工作尺寸
型腔的計(jì)算
型腔徑向尺寸
型腔高度尺寸
3.5
2.5
2
型芯的計(jì)算
型芯的計(jì)算
型芯徑向尺寸
型芯高度尺寸
1.5
型孔中心
距
(表3-1)型芯和型腔計(jì)算
3.2 型腔厚度和底板厚度的確定
根據(jù)放大鏡型腔的形狀以及其合理性選擇型腔壁厚和底板厚度，具體厚度見(jiàn)（圖3-3模架圖）
3.3確定零件結(jié)構(gòu)及尺寸
經(jīng)初步排祥預(yù)算預(yù)選模架為2025-AI-30-30-70模架 即200×250×210mm
具體尺寸如下：
定模底板厚： 25
定模板厚： A=30
動(dòng)模板厚: B=30
支撐板： 30
墊塊厚度: C=70
下模座厚： 25
模具厚度：
模具外形尺寸： 200×250×210
如下圖所示：
（圖3-3）（模架草圖）
3.3.1定模座板設(shè)計(jì)：
外形尺寸：250×250×25mm；材料：45#；調(diào)質(zhì)HB216-260；澆口套與板之間采用φ20H7/k6過(guò)渡配合，中間8個(gè)螺釘為M10×30，外面4個(gè)為M12×30孔距為130×160mm。如圖（4-4）
（圖3-4）（定模痤板初步設(shè)計(jì)圖）
3.3.2定模型腔固定板設(shè)計(jì)：
外形尺寸：250×200×30mm；材料：45#；淬火50HRC；外面點(diǎn)的4個(gè)孔為導(dǎo)套φ20孔距為204×154mm；中間點(diǎn)的4個(gè)螺紋孔M12×30孔距為130×160mm；中間的方形為150×130mm如圖（4-5）
（圖3-5）（定模型腔固定板）
3.3.3 動(dòng)模型腔固定板設(shè)計(jì)：
外形尺寸：250×200×30mm；材料：45#；淬火50HRC；4個(gè)為導(dǎo)套孔φ20孔距為204×154mm；4個(gè)螺紋孔M12×30孔距為130×160mm；中間的方形為150×130mm；比定模型腔固定板多的中間2個(gè)孔為定位銷φ15。如圖（4-6）
（圖3-6）（動(dòng)模型腔固定板）
3.3.4 支撐板設(shè)計(jì)設(shè)計(jì)：
外形尺寸：250×200×30mm；材料：45#；淬火50HRC；4個(gè)復(fù)位桿孔φ20孔距為200×80mm；8個(gè)螺紋孔M10×30孔距；2個(gè)型腔桿孔φ42間距為68×50mm；中間一個(gè)為推桿孔φ8。如圖（4-7）
（圖3-7）（支撐板）
3.3.5 推桿固定板設(shè)計(jì)：
外形尺寸：250×120×15mm；材料：45#；調(diào)質(zhì)30HRC；4個(gè)復(fù)位桿孔φ20孔距為200×80mm；4個(gè)螺紋孔M8×25孔距230×98；2個(gè)型腔桿孔φ42間距為68×50mm；中間一個(gè)為推桿孔φ8。如下圖（4-8）
（圖3-8）（推桿固定板）
第四章 注塑機(jī)的選定
4.1計(jì)算澆注系統(tǒng)體積
由澆注系統(tǒng)體積得澆注系統(tǒng)質(zhì)量為:
式中：——————橫向澆注體積
——————縱向澆注體積
——————澆注系統(tǒng)總體積
——————澆注系統(tǒng)總質(zhì)量
4.2注塑機(jī)選定
注射機(jī)額定注射量，每次注射量不超過(guò)最大注射量的80%
即
式中n－型腔數(shù)
－澆注系統(tǒng)重量(g)
－塑件重量(g)
－注射機(jī)額定注射量(g)
因n=2得：
故
故
再根據(jù)塑料制品的體積或質(zhì)量以及塑件形狀一般，塑件熔體粘度一般，所需注射壓力通常為100-140MPa。查教材（塑料成型工藝與模具設(shè)計(jì)表4.2）或有關(guān)手冊(cè)選定注射機(jī)型號(hào)為：
XS-ZY-125
注塑機(jī)的參數(shù)如下：
注塑機(jī)最大注塑量：125cm3；鎖模力：900kN；
注塑壓力：120Mpa； 最小模厚：200mm；
開(kāi)模行程：300mm； 注塑機(jī)定位孔直徑：100mm；
噴嘴前端孔徑：4mm； 噴嘴球面半徑：SR12mm；
注塑機(jī)拉桿的間距：260×290/mm×mm。
第五章 校核注射機(jī)有關(guān)工藝參數(shù)
5.1最大注塑量參數(shù)校核
注塑機(jī)的最大注塑量應(yīng)大于制品的質(zhì)量或體積（包括流道及澆口凝料和飛邊），通常注塑機(jī)的實(shí)際注塑量最好在注塑機(jī)的最大注塑量的80%。并且此次的模具為一模二腔，所以，選用的注塑機(jī)最大注塑量應(yīng)：
式中：——注塑機(jī)的最大注塑量，g；
——塑件的體積，g該產(chǎn)品=26.3g；
——澆注系統(tǒng)體積，g，該產(chǎn)品=6.5g
；
故：
此處選定的注塑機(jī)滿足注射量校核要求。
5.2鎖模力校核
式中 ——熔融塑料在分型面上的漲開(kāi)力，N。；
——塑料熔體對(duì)型腔的成型壓力，MPa，其大小一般是注射壓力的80%，注
射壓力大小上面注塑機(jī)的參數(shù)已寫(xiě)；
n——型腔的數(shù)量；
——單個(gè)塑件在模具分型面上的投影面積，mm2
——澆注系統(tǒng)在模具分型面上的投影面積，mm2
——注射機(jī)的額定鎖模力，N。；
故： ；此注塑機(jī)滿足鎖模力要求。
5.3、模具厚度H與注射機(jī)閉合高度
5.3.1模具閉合高度長(zhǎng)寬尺寸要與注塑機(jī)模板尺寸和推桿間距相適應(yīng)：
模具長(zhǎng)×寬<拉桿面積；
即200×250<推桿間距（260×290）
5.3.2由于此次采用的是單分型面，注射機(jī)開(kāi)模行程應(yīng)大于模具開(kāi)模時(shí)取出塑件（包括澆注
系統(tǒng)）所需的開(kāi)模距，
即滿足下式：
式中 ——注射機(jī)最大開(kāi)模行程，300mm；
——模具實(shí)際高度；
——注射機(jī)最小閉合尺寸
——推出距離（脫模距離），15mm；
——塑料高度（包括澆注系統(tǒng)在內(nèi)），74mm；
則：
故：此注塑機(jī)滿足開(kāi)模行程的較核要求。
結(jié)束語(yǔ)
這次模具設(shè)計(jì)是第二次設(shè)計(jì)，通過(guò)這次設(shè)計(jì)，讓我對(duì)大學(xué)三年的模具學(xué)習(xí)生涯有了一個(gè)總結(jié)，更讓我了解了該怎么樣去設(shè)計(jì)一個(gè)模具，設(shè)計(jì)模具圖時(shí)，在理解了模具的功能和大致的輪廓后，最重要的是在設(shè)計(jì)的時(shí)候能夠細(xì)心，做到照顧到模具的各個(gè)方面的問(wèn)題，要想到設(shè)計(jì)出來(lái)的模具能不能制造出來(lái)，合不合理，
能不能更好的節(jié)省材料等問(wèn)題，在以后的設(shè)計(jì)模具時(shí)，自己就知道怎樣能不能更好的節(jié)省材料等問(wèn)題，在以后的設(shè)計(jì)模具時(shí)，自己就知道怎樣去設(shè)一個(gè)模具，此次設(shè)計(jì)使我收獲很多……
參考文獻(xiàn)
[1]屈華昌主編.《塑料成型工藝與模具設(shè)計(jì)》.北京:高等教育出版社,2001
[2]李澄,吳天生,聞百橋主編.《機(jī)械制圖》.北京:高等教育出版社,1997
[3]《塑料模設(shè)計(jì)手冊(cè)》編寫(xiě)組主編.《塑料模設(shè)計(jì)手冊(cè)》(第二版).北京:機(jī)械工業(yè)出版社,2002
[4]許發(fā)樾主編.《實(shí)用模具設(shè)計(jì)與制造手冊(cè)》.北京：機(jī)械工業(yè)出版社，2002
[5]吳兆祥主編.《模具材料及表面處理》.北京:機(jī)械出版社,2000
[6]陳于萍主編.《互換性與測(cè)量技術(shù)基礎(chǔ)》.北京:機(jī)械工業(yè)出版社,2001
[7]馮炳堯，韓泰榮，將文森主編《模具設(shè)計(jì)與制造簡(jiǎn)明手冊(cè)》，上?？茖W(xué)技術(shù)
Single gate optimization for plastic injection mold
Journal of Zhejiang University - Science A
Volume 8, Number 7 (2007), 1077-1083, DOI: 10.1631/jzus.2007.A1077
Ji-quan Li, De-qun Li, Zhi-ying Guo and Hai-yuan Lv
Abstract:
Abstract: This paper deals with a methodology for single gate location optimization for plastic injection mold. The objective of the gate optimization is to minimize the warpage of injection molded parts, because warpage is a crucial quality issue for most injection molded parts while it is influenced greatly by the gate location. Feature warpage is defined as the ratio of maximum displacement on the feature surface to the projected length of the feature surface to describe part warpage. The optimization is combined with the numerical simulation technology to find the optimal gate location, in which the simulated annealing algorithm is used to search for the optimum. Finally, an example is discussed in the paper and it can be concluded that the proposed method is effective.
Key words: Injection mold, Gate location, Optimization, Feature warpage.
INTRODUCTION
Plastic injection molding is a widely used, com- plex but highly efficient technique for producing a large variety of plastic products, particularly those with high production requirement, tight tolerance, and complex shapes. The quality of injection molded parts is a function of plastic material, part geometry, mold structure and process conditions. The most important part of an injection mold basically is the following three sets of components: cavities, gates and runners, and cooling system.
Lam and Seow (2000) and Jin and Lam (2002) achieved cavity balancing by varying the wall thick- ness of the part. A balance filling process within the cavity gives an evenly distributed pressure and tem- perature which can drastically reduce the warpage of the part. But the cavity balancing is only one of the important influencing factors of part qualities. Espe- cially, the part has its functional requirements, and its thicknesses should not be varied usually.
From the pointview of the injection mold design, a gate is characterized by its size and location, and the runner system by the size and layout. The gate size and runner layout are usually determined as constants. Relatively, gate locations and runner sizes are more flexible, which can be varied to influence the quality of the part. As a result, they are often the design pa- rameters for optimization.
Lee and Kim (1996a) optimized the sizes of runners and gates to balance runner system for mul- tiple injection cavities. The runner balancing was described as the differences of entrance pressures for a multi-cavity mold with identical cavities, and as differences of pressures at the end of the melt flow path in each cavity for a family mold with different cavity volumes and geometries. The methodology has shown uniform pressure distributions among the cavities during the entire molding cycle of multiple cavities mold.
Zhai et al.(2005a) presented the two gate loca- tion optimization of one molding cavity by an effi- cient search method based on pressure gradient (PGSS), and subsequently positioned weld lines to the desired locations by varying runner sizes for multi-gate parts (Zhai et al., 2006). As large-volume part, multiple gates are needed to shorten the maxi- mum flow path, with a corresponding decrease in injection pressure. The method is promising for de- sign of gates and runners for a single cavity with multiple gates.
Many of injection molded parts are produced with one gate, whether in single cavity mold or in multiple cavities mold. Therefore, the gate location of a single gate is the most common design parameter for optimization. A shape analysis approach was pre- sented by Courbebaisse and Garcia (2002), by which the best gate location of injection molding was esti- mated. Subsequently, they developed this methodol- ogy further and applied it to single gate location op- timization of an L shape example,(Courbebaisse,2005). It is easy to use and not time-consuming, while it only serves the turning of simple flat parts with uniform thickness.
Pandelidis and Zou (1990) presented the opti- mization of gate location, by indirect quality measures relevant to warpage and material degradation, which is represented as weighted sum of a temperature dif- ferential term, an over-pack term, and a frictional overheating term. Warpage is influenced by the above factors, but the relationship between them is not clear. Therefore, the optimization effect is restricted by the determination of the weighting factors.
Lee and Kim (1996b) developed an automated selection method of gate location, in which a set of initial gate locations were proposed by a designer and then the optimal gate was located by the adjacent node evaluation method. The conclusion to a great extent depends much on the human designer’s intuition, because the first step of the method is based on the designer’s proposition. So the result is to a large ex- tent limited to the designer’s experience.
Lam and Jin (2001) developed a gate location optimization method based on the minimization of the Standard Deviation of Flow Path Length (SD[L]) and Standard Deviation of Filling Time (SD[T]) during the molding filling process. Subsequently, Shen et al.(2004a; 2004b) optimized the gate location design by minimizing the weighted sum of filling pressure, filling time difference between different flow paths, temperature difference, and over-pack percentage. Zhai et al.(2005b) investigated optimal gate location with evaluation criteria of injection pressure at the end of filling. These researchers presented the objec- tive functions as performances of injection molding filling operation, which are correlated with product qualities. But the correlation between the perform- ances and qualities is very complicated and no clear relationship has been observed between them yet. It is also difficult to select appropriate weighting factors for each term.
A new objective function is presented here to evaluate the warpage of injection molded parts to optimize gate location. To measure part quality di- rectly, this investigation defines feature warpage to evaluate part warpage, which is evaluated from the “flow plus warpage” simulation outputs of Moldflow Plastics Insight (MPI) software. The objective func- tion is minimized to achieve minimum deformation in gate location optimization. Simulated annealing al- gorithm is employed to search for the optimal gate location. An example is given to illustrate the effec- tivity of the proposed optimization procedure.
QUALITY MEASURES: FEATURE WARPGE
Definition of feature warpage
To apply optimization theory to the gate design, quality measures of the part must be specified in the first instance. The term “quality” may be referred to many product properties, such as mechanical, thermal, electrical, optical, ergonomical or geometrical prop- erties. There are two types of part quality measures: direct and indirect. A model that predicts the proper- ties from numerical simulation results would be characterized as a direct quality measure. In contrast, an indirect measure of part quality is correlated with target quality, but it cannot provide a direct estimate of that quality.
For warpage, the indirect quality measures in related works are one of performances of injection molding flowing behavior or weighted sum of those. The performances are presented as filling time dif- ferential along different flow paths, temperature dif- ferential, over-pack percentage, and so on. It is ob- vious that warpage is influenced by these perform- ances, but the relationship between warpage and these performances is not clear and the determination of these weighting factors is rather difficult. Therefore, the optimization with the above objective function probably will not minimize part warpage even with perfect optimization technique. Sometimes, improper weighting factors will result in absolutely wrong re- sults.
Some statistical quantities calculated from the nodal displacements were characterized as direct quality measures to achieve minimum deformation in related optimization studies. The statistical quantities are usually a maximum nodal displacement, an av- erage of top 10 percentile nodal displacements, and an overall average nodal displacement (Lee and Kim,
1995; 1996b). These nodal displacements are easy to obtain from the simulation results, the statistical val- ues, to some extents, representing the deformation. But the statistical displacement cannot effectively describe the deformation of the injection molded parts.
In industry, designers and manufacturers usually pay more attention to the degree of part warpage on some specific features than the whole deformation of the injection molded parts. In this study, feature warpage is defined to describe the deformation of the injection parts. The feature warpage is the ratio of the maximum displacement of the feature surface to the projected length of the feature surface (Fig.1):
where γ is the feature warpage, h is the maximum displacement on the feature surface deviating from the reference platform, and L is the projected length of the feature surface on a reference direction paralleling the reference platform.
For complicated features (only plane feature discussed here), the feature warpage is usually separated into two constituents on the reference plane, which are represented on a 2D coordinate system:
where γx, γy are the constituent feature warpages in the X, Y direction, and Lx, Ly are the projected lengths of the feature surface on X, Y component.
Evaluation of feature warpage
After the determination of target feature com- bined with corresponding reference plane and pro- jection direction, the value of L can be calculated immediately from the part with the calculating method of analytic geometry (Fig.2). L is a constant for any part on the specified feature surface and pro- jected direction. But the evaluation of h is more com- plicated than that of L.
Simulation of injection molding process is a common technique to forecast the quality of part de- sign, mold design and process settings. The results of warpage simulation are expressed as the nodal de- flections on X, Y, Z component (Wx, Wy, Wz), and the nodal displacement W. W is the vector length of vector sum of Wx·i, Wy·j, and Wz·k, where i, j, k are the unit vectors on X, Y, Z component. The h is the maximum displacement of the nodes on the feature surface, which is correlated with the normal orientation of the reference plane, and can be derived from the results of warpage simulation.
To calculate h, the deflection of its node is evaluated firstly as follows:
where Wi is the deflection in the normal direction of the reference plane of ith node; Wix, Wiy, Wiz are the deflections on X, Y, Z component of ith node; α, β, γ are the angles of normal vector of the reference; A and B are the terminal nodes of the feature to projectingdirection (Fig.2); WA and WB are the deflections of nodes A and B:
where WAx, WAy, WAz are the deflections on X, Y, Z
component of node A; WBx, WBy and WBz are the de- flections on X, Y, Z component of node B; ωiA and ωiB are the weighting factors of the terminal node deflections calculated as follows:
where LiA is the projector distance between ith node and node A. Ultimately, h is the maximum of the absolute value of Wi:
In industry, the inspection of the warpage is carried out with the help of a feeler gauge, while the measured part should be placed on a reference plat- form. The value of h is the maximum numerical reading of the space between the measured part surface and the reference platform.
GATE LOCATION OPTIMIZATION PROBLEM FORMATION
The quality term “warpage” means the perma- nent deformation of the part, which is not caused by an applied load. It is caused by differential shrinkage throughout the part, due to the imbalance of polymer flow, packing, cooling, and crystallization.
The placement of a gate in an injection mold is one of the most important variables of the total mold design. The quality of the molded part is greatly af- fected by the gate location, because it influences the manner that the plastic flows into the mold cavity. Therefore, different gate locations introduce inho- mogeneity in orientation, density, pressure, and temperature distribution, accordingly introducing different value and distribution of warpage. Therefore, gate location is a valuable design variable to minimize the injection molded part warpage. Because the correlation between gate location and warpage distribu- tion is to a large extent independent of the melt and mold temperature, it is assumed that the moldingconditions are kept constant in this investigation. The injection molded part warpage is quantified by the feature warpage which was discussed in the previous section.
The single gate location optimization can thus be formulated as follows:
Minimize:
Subject to:
where γ is the feature warpage; p is the injection pressure at the gate position; p0 is the allowable in- jection pressure of injection molding machine or the allowable injection pressure specified by the designer or manufacturer; X is the coordinate vector of the candidate gate locations; Xi is the node on the finite element mesh model of the part for injection molding process simulation; N is the total number of nodes.
In the finite element mesh model of the part, every node is a possible candidate for a gate. There- fore, the total number of the possible gate location Np is a function of the total number of nodes N and the total number of gate locations to be optimized n:
In this study, only the single-gate location problem is investigated.
SIMULATED ANNEALING ALGORITHM
The simulated annealing algorithm is one of the most powerful and popular meta-heuristics to solve optimization problems because of the provision of good global solutions to real-world problems. The algorithm is based upon that of Metropolis et al. (1953), which was originally proposed as a means to find an equilibrium configuration of a collection of atoms at a given temperature. The connection between this algorithm and mathematical minimization was first noted by Pincus (1970), but it was Kirkpatrick et al.(1983) who proposed that it formed the basis of an optimization technique for combinational (and other) problems.
To apply the simulated annealing method to op timization problems, the objective function f is used as an energy function E. Instead of finding a low energy configuration, the problem becomes to seek an approximate global optimal solution. The configura- tions of the values of design variables are substituted for the energy configurations of the body, and the control parameter for the process is substituted for temperature. A random number generator is used as a way of generating new values for the design variables. It is obvious that this algorithm just takes the mini- mization problems into account. Hence, while per- forming a maximization problem the objective func- tion is multiplied by (?1) to obtain a capable form.
The major advantage of simulated annealing algorithm over other methods is the ability to avoid being trapped at local minima. This algorithm employs a random search, which not only accepts changes that decrease objective function f, but also accepts some changes that increase it. The latter are accepted with a probability p
where ?f is the increase of f, k is Boltzman’s constant, and T is a control parameter which by analogy with the original application is known as the system “temperature” irrespective of the objective function involved.
In the case of gate location optimization, the implementation of this algorithm is illustrated in Fig.3, and this algorithm is detailed as follows:
(1) SA algorithm starts from an initial gate loca- tion Xold with an assigned value Tk of the “temperature” parameter T (the “temperature” counter k is initially set to zero). Proper control parameter c (0
收藏