CA6140手柄轴的加工工艺及夹具设计【钻8.5螺纹孔】【说明书+CAD】
CA6140手柄轴的加工工艺及夹具设计【钻8.5螺纹孔】【说明书+CAD】,钻8.5螺纹孔,说明书+CAD,CA6140手柄轴的加工工艺及夹具设计【钻8.5螺纹孔】【说明书+CAD】,ca6140,手柄,加工,工艺,夹具,设计,螺纹,罗纹,说明书,仿单,cad
机械加工工艺过程卡片机械加工工艺过程卡片产品型号CA6140零(部件)图号产品名称车床零(部件)名称共一页第一页材料牌号45钢毛坯种类模锻件毛坯外型尺寸44mm126mm每毛坯可制件数1每台件数1备注工序号工序名称工序内容车间工段设备工艺装备工时/s准终单件正火2粗车粗车小端面;粗车外圆17.2mm,20mm;粗车沟槽3mm2.15mm,车沟槽1.5mm1mm,3mm0.5mmCM6125机床三爪自定心卡盘1073粗车粗车大端面及41mm的外圆CM6125机床三爪自定心卡盘1194半精车半精车小端面,半精车外圆17.2mm,20mm,半精车沟槽3mm2.15mm,车倒角CM6125机床三爪自定心卡盘1205精车精车外圆17.2mm,20mmCM6125机床三爪自定心卡盘1156粗车粗车圆锥面CM6125机床三爪自定心卡盘1367半精车半精车圆锥面CM6125机床三爪自定心卡盘顶1158精车精车圆锥面CM6125机床三爪自定心卡盘1569抛光圆锥面抛光18510镀铬圆锥面镀铬13211钻孔钻14mm ,8.5mm的孔Z518钻床专用夹具10512扩孔扩14mm ,8.5mm的孔Z518钻床专用夹具18013攻螺纹攻M10螺纹专用夹具11814粗铣粗铣键槽5mm3mm14mmX62卧式铣床专用夹具16915半精铣半精铣5mm3mm14mmX62卧式铣床专用夹具12816去毛刺去除全部毛刺钳工台17终检按零件图样要求全面检查机械加工工序2卡片机械加工工序卡片产品型号CA6140零(部件)图号手柄轴产品名称车床零(部件)名称 第一页车间工序号工序名材料牌号2粗车45钢毛坯种类毛坯外型尺寸每毛坯可制件数每件台数模锻件44mm126mm11设备名称设备型号设备编号同时加工件数卧式车床CM61251夹具编号夹具名称切削液三爪自定心卡盘, 工位器具编号工位器具名称工序时间/s准终单件119工序步 工步内容工艺装备主轴转速/r.s-1切削速度/m.s-1进给量/mm.r-1背吃刀量/mm进给次数工步工时/s机动辅助 1 车小端面,保持尺寸mmYT5 90偏刀,游标卡尺161.10.21.516 2 车外圆19.2mm171.10.4114 3 车外圆 mm171.10.40.8114 4 车沟槽保持尺寸3mm2,775mm,及 61.5mm100.58手动0.715车沟槽保持尺寸1.5mm1mm 及 3mm100.58手动16车沟槽保持尺寸3mm0.5mm及 20.5mm,102.5mm100.58手动1机械加工工序5卡片机械加工工序卡片产品型号CA6140零(部件)图号产品名称车床零(部件)名称 第一页车间工序号工序名材料牌号5粗车45钢毛坯种类毛坯外型尺寸每毛坯可制件数每件台数模锻件44mm126mm11设备名称设备型号设备编号同时加工件数卧式车床CM61251夹具编号夹具名称切削液三爪自定心卡盘工位器具编号工位器具名称工序时间/s准终单件119工序步 工步内容工艺装备主轴转速/r.s-1切削速度/m.s-1进给量/mm.r-1背吃刀量/mm进给次数工步工时/s机动辅助 1 精车外圆17.2mmYT30 90偏刀,游标卡尺402.030.20.4514 2 精车外圆mm332.030.20.45113 课 程 设 计 说 明 书 机械制造技术基础设计题目:手柄轴(CA6140车床)的加工工艺钻8.5螺纹孔的钻床夹具设计学院:机械工程学院班级:机自0606学号:姓名: 指导:薛国祥老师题目:设计“手柄轴(CA6140车床)”零件的机械加工工艺规程及相关工序内容:零件图 1张 毛坯图 1张 机械加工工艺过程卡片 1张 机械加工工序卡片 2张夹具装配图 1张夹具体零件图 1张课程设计说明书 1份目录一、 零件的工艺分析及生产类型的确定1. 零件的作用- 3 2. 热处理- 33. 零件的生产类型- 3二、选择毛坯,确定毛坯尺寸,设计毛坯图1.选择毛坯- 32.确定机械加工余量、毛胚尺寸和公差- 33.确定机械加工余量- 44确定毛坯尺-45.确定毛坯尺寸公差-56.设计毛坯图-5三、选择加工方法,制定工艺路线1.定位基准的选择-62.零件表面加工方法的选择-63.制定工艺路线-6四、工序设计1.选择加工设备与工艺装备-82.确定工序尺寸-9五、确定切削用量及基本时间-11六、夹具设计-20七 参考文献-22 一 零件的工艺分析及生产类型的确定1. 零件的工艺性分析 通过对该零件图的重新绘制,知原图样的视图正确,完整,尺寸,公差及技术要求齐全。该零件属轴类回转体零件,它的所有表面均需切屑加工,各表面的加工精度和表面粗糙度都不难获得。 表面粗糙度要求较高 需经多次切削才能满足要求,手柄处镀铬,在镀铬之前须进行抛光处理以使镀铬均匀。本零件的最难加工的地方就是在斜面上钻孔,且要保证孔与键槽成,需要专用夹具。总体来说,本零件的工艺性较好。2. 零件的生产类型 依设计的题目知:生产纲领 N = 30000万/年 , 生产类型为大批大量生产 零件是机床CA6140的手柄轴,质量为0.445Kg.二 选择毛坯,确定毛坯尺寸,设计毛坯图1. 选择毛坯该材料为45钢。该零件在工作过程中则经常承受交变载荷,因此应选用锻件,以使金属纤维尽量不被切断,保证零件工作可靠。零件属批量生产,而且零件的轮廓尺寸不大,故采用摸锻成型。这从提高生产率,保证加工精度上考虑,也是应该的。2确定机械加工余量,毛坯尺寸和公差钢质摸锻件的公差及机械加工余量按GB/T12362-2003确定。要确定毛坯尺寸公差及机械加工余量,应先确定如下各项因素。(1) 锻件公差等级 由该零件的功用和技术要求,确定其锻件公差等级为普通级。(2) 锻件质量Mf 根据零件0.445kg,估算为mf=1.0kg.(3) 锻件形状复杂系数S S=Mf/Mn 该锻件为圆形,假设其最大直径为46mm,长126mm Mn = 1.6kg S = 1/1.6 = 0.62故该零件的形状复杂系数S属S2级。(4) 锻件材质系数M 由于该零件材料为45钢,是碳的质量分数小于0.65%的碳素钢,故该锻件的材质系数属M1级。(5) 零件表面粗糙度 由零件图可知,除17.2mm, 15.7mm 粗糙度Ra = 1.6,圆锥面处Ra=0.8,其余均为6.3。 3. 确定机械加工余量 根据锻件质量,零件表面粗糙度,形状复杂系数查表5-9,由此得单边余量在厚度方向为1.7-2.2mm,水平方向亦为1.7-2.2mm,即锻件各外径的单面余量为1.7-2.2mm,各轴向尺寸的单面余量为1.7-2.2mm。 4 确定毛坯尺寸 上面查的加工余量适用于机械加工表面粗糙度Ra大于等于1.6m。Ra小于1.6m的表面,余量要适当加大。分析本零件,除17.2mm, 15.7mm 粗糙度Ra = 1.6, 其余均为6.3,因此这些表面的毛坯尺寸只需将零件的尺寸加上所查的余量即可。综上所述,确定毛坯尺寸见下表 手柄轴毛坯(锻件)尺寸零件尺寸单面加工余量锻件尺寸17.2221.2224大端40圆锥面2445. 确定毛坯尺寸公差毛坯尺寸公差根据锻件质量,材质系数,形状复杂系数从表5-6,表5-7中查的。本零件毛坯尺寸允许偏差见下表 手柄轴毛坯(锻件)尺寸允许偏差锻件尺寸偏差根据21.2 表5-6244422表5-7102126 6 设计毛坯图(1) 确定圆角半径 锻件的外圆角半径按表5-12确定,内圆角半径按表5-13确定。分析本锻件可确定外圆角R2, R3内圆角R3(2) 确定模锻斜度 按表5-11,外模锻斜度= 3(3)确定分模位置由于毛坯为轴类锻件,应采取轴向分模。为了便于起模及便于发现上,下模在模锻过程中的错移,选择最大直径即圆锥面处的对称平面为分模面,分模线为直线,属平直分模线。(4)确定毛坯的热处理方式钢质毛坯经锻造后应安排正火,以消除残余的锻造应力,并使不均匀的金相组织通过重新结晶而得到细化,均匀的组织,从而改善加工性。三 选择加工方法,制定工艺路线1.定位基准的选择以44的外圆和端面为粗基准,以17.2的外圆和端面为精基准。2.零件表面加工方法的选择本零件的加工面有外圆,端面,键槽,倒角,倒圆,沟槽,锥面,孔,螺纹。(1)17.2的外圆面,未标注公差尺寸,表面粗糙度Ra 1.6,需要粗车,半精车,精车(2)20的外圆,公差等级IT6,需要粗车,半精车,精车。(3)圆锥面,为保证镀铬均匀,在镀铬之前圆锥面需要粗车,半精车,精车,保证Ra = 1.6 然后抛光。(4)槽3x2.15 表面粗糙度为Ra3.2,需要粗车,半精车 槽1.5x1 表面粗糙度为Ra6.3,粗车即可。 槽3x0.5 表面粗糙度为Ra6.3,粗车即可(5) 两孔的表面粗糙度Ra6.3 需钻,扩(6)键槽5314 粗糙度Ra6.3 需要粗铣,半精铣。(7)端面 本零件为回转体端面,尺寸精度要求不高,所以大端面粗车即可满足要求,但是小端面作为精基准应该粗车,半精车3制定工艺路线方案一工序1 正火工序2 以20mm处的外圆及端面定位,车大端面,粗车41的外圆工序3 以粗车后的40mm处外圆面及端面定位,粗车另一端面,粗车17.2mm的外圆,粗车20mm的外圆,车1.5mm1mm沟槽,粗车3mm0.5mm沟槽,粗车3mm2.15mm沟槽工序4 以粗车的20mm的外圆及端面定位 ,半精车,精车40mm的外圆。工序5 以精车后的40mm的外圆及端面定位,半精车,17.2mm的外圆,半精车20mm的外圆,半精车3mm2.15mm的沟槽工序6 精车17.2mm的外圆,精车20mm的外圆,车倒角。工序7 以20mm的外圆定位,粗车,半精车,精车圆锥面。工序8 粗铣,半精铣键槽工序9 抛光工序10 镀铬工序11 钻,扩14mm孔及 8.5mm的螺纹孔工序12 攻螺纹工序13 去毛刺工序14 终检 方案 二工序1 正火工序2 粗车小端面,粗车17.2mm的外圆,粗车20mm的外圆粗车,车1.5mmx1mm沟槽,粗车3mmx0.5mm沟槽,粗车3mm2.15mm沟槽工序3 粗车大端面及41mm的外圆工序4 半精车小端面,半精车,17.2mm的外圆,半精车20mm的外圆,半精车3mm2.15mm的沟槽,车倒角工序5 精车17.2mm的外圆,精车20mm的外圆工序6 以加工过的20mm外圆及端面定位,粗车圆锥面工序7 半精车圆锥面工序8 精车圆锥面工序9 抛光工序10 镀铬工序11 钻14mm的孔和8.5mm的螺纹孔工序12 扩14mm的孔和8.5mm的螺纹孔工序13 攻M10的螺纹工序14 以20mm圆柱面及端面定位铣键槽5mm3mm14mm工序15 去毛刺工序16 终检方案比较:方案二比方案一更容易保证尺寸精度,方案二以车过的41mm的外圆定位保证了定位精度,方案一的小端面知粗车一次可能不能保证要求的表面粗糙度,方案一的粗加工,精加工拍的比较混乱,不符合加工要求。 综上所述,工艺路线应选择方案二。四 工序设计1 选择加工设备与工艺装备(1) 选择机床 根据不同的工序选择机床。a 工序1-8是粗车合半精车。各工序的工步数不多,成批生产不要求很高的生产率,故选用卧式车床就能满足要求。本零件外廓尺寸不大,精度要求不是很高,选CM6125即可。b 工序11 钻孔,可采用专用夹具在立式钻床上加工,故选Z525型立式钻床。c 工序14是用整体硬质合金直柄立铣刀粗铣,半精铣键槽,用选用卧式铣床。考虑本零件属成批生产,所选机床使用范围较广为宜,故选常用的X62型铣床能满足加工要求。d 工序13攻螺纹,需要丝锥。 ( 2 ) 选择夹具本零件处粗铣及半精铣槽,钻孔等工序需要专用夹具外,其他工序使用通用夹具即可,选用三抓自定心卡盘。(3) 选择刀具 根据不同的工序选择刀具 A 在车床上的加工工序,一般选用硬质合金车刀。加工钢质零件采用YT类硬质合金,粗加工用YT5,半精加工用YT15,精加工用YT30.为提高生产率及经济性,应选用可转位车刀(GB5343.1-1985,GB5343.2-1985). B 铣刀按表5-104选直柄键槽铣刀键槽bxh=5mmx3mm,半精铣铣刀选择直径d = 5 mm l = 8mm L = 52mm由于粗铣后宽度方向单边余量1mm,故粗铣时的铣刀选择d=3mm l =5mm L =37mm C 钻头的选择(a) 14mm的孔 扩孔选择直柄扩孔钻 d = 14mm,L =160mm l=108mm钻孔是直径方向的余量4mm,所以钻孔时选择直柄麻花钻d = 13mm l= 151mm l1 = 101mm(b) 8.5mm的孔 扩孔选择直柄扩孔钻d = 8.8mm L=125mm l =81mm钻孔时直径方向余量1.5 mm ,选用直柄麻花钻 d =7mm l =109mm l1=69mm(4) 选择量具本零件属成批生产,一般情况下尽量采用通用量具。根据零件表面的精度要求,尺寸和形状特点,选择如下。a 选择外圆量具 外圆可选用读数值0.02,测量范围0150游标卡尺(表5-108)b 选择加工轴向尺寸所用量具 轴向尺寸所用量具可选用读数值0.05,测量范围0150游标卡尺(表5-108)选择加工槽所用量具c 选择加工槽所用量具 槽经粗铣,半精铣两次加工。槽宽及槽深的尺寸公差的等级为:粗铣时均为IT14;半精铣时 ,槽宽IT13,槽深为IT14.。均可选用读数值为0.02mm,测量范围0150mm的游标卡尺进行测量。2 确定工序尺寸(1)确定圆柱面的工序尺寸 圆柱面多次加工的工序至于加工余量有关。本零件个圆柱表面的工序加工余量,工序尺寸及公差,表面粗糙度见下表 圆柱表面的工序加工余量,工序尺寸及公差,表面粗糙度 /mm加工表面工序双边余量工序尺寸及公差表面粗糙度及经济加工精度粗车半精车精车粗车半精车精车粗车半精车精车17.2mm外圆21.10.917.2IT13Ra 6.3IT11Ra 3.2IT6Ra 1.620g6mm外圆1.61.50.9IT13Ra 6.3IT11Ra 3.2IT6Ra 1.641mm外圆3_41_IT13Ra 6.3_(2) 确定各孔的工序尺寸加工对象工序双边余量工序尺寸及公差钻扩钻扩14mm孔1318.5mm孔71.5 (3) 确定各端面工序加工余量 /mm工序加工表面总加工余量工序加工余量2小端面21.53大端面224小端面20.5 (4) 确定轴向尺寸 a 第一段17.2mm的长度L1,由尺寸链可得 L1 = 2mmb 第二段17.2mm的长度L2,求解尺寸链可得 L2 = 12.5mm c 第二段20mmm的长度L3,由尺寸链可得 L3 = d 圆锥面处的轴向长度L4, 由尺寸链可得 L4 = (5) 确定铣槽的工序尺寸 半精铣即可达到零件图样的要求,槽宽5mm, 粗铣后半精铣的余量1.5mm, 所以粗铣的宽度工序尺寸3.5mm(6) 圆锥面抛光直径余量 0.1mm五 确定切削用量及基本时间切削用量包括背吃刀量 ,进给量f和切削速度v。确定顺序是先确定,f,再确定v。1. 工序3切削用量及基本时间的确定 (1) 切削用量 本工序为粗车(车端面和外圆)。已知材料为45钢,= 670MPa,锻件,有外皮;机床为CM6125型卧式车床,工件装卡在三爪自定心卡盘中。确定粗车外圆41mm的切削用量。所选刀具为YT5硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 90 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm a 确定背吃刀量 粗车双边余量为3.0mm 所以 1.5mm b 确定进给量f 根据表5-114,在粗车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm f= 0.4-0.5mm/r 按CM6125车床的进给量,选择f =0.4 mm/r确定的进给量尚需满足机床进给机构的轻度要求,故需进行校验。根据表5-123,当钢料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 预计是进给力为760N修正系数 =1.0 =1.0 =1.17 故实际进给力为889.2N,满足要求。c 选择刀具磨钝标准及耐用度 根据表5-119,车刀后刀面的最大磨损量为1mm,可转位车刀耐用度T =30min d 确定切削速度V 根据表5-120,当用YT5硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 140m/min切削速度的修正系数为 = 0.8 = 0.65 =0.81 =1.15 = =1.0 故V = 1400.80.650.811.15 = 67.8m/minn = 1000v/d = 1000 67.8/3.14 44 = 491 r/min按CM6125车床的转速,选择 n = 500 r/min e 校验机床功率 当钢料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min时, = 1.7KW切削功率的修正系数为=1.17 = = =1.0 =1.13 =0.8 =0.65故实际切削功率为 =0.72KW满足要求。最后确定的切削用量为 := 1.5 mm f = 0.4mm/r n = 480r/min v = 66.3 m/min (2) 基本时间 a 确定粗车41mm的外圆基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=20mm = 2mm = 3mm = 0 f = 0.4mm/r n= 8r/min i = 1所以Tj1= 8 S b 确定车端面的基本时间 Tj2 =i L/fn L = (dd1) + + + d = 44mm = 2mm = 4mm = 0所以 Tj2 = 18S因此,总的切削基本时间为26S. 2 工序2切削用量确定(1) 确定粗车19.2mm 外圆的切削用量所选刀具为YT5硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 90 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm (a) 确定背吃刀量 粗车双边余量为2mm 所以 = 1mm (b ) 确定进给量f 根据表5-114,在粗车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm f= 0.4-0.5mm/r 按CM6125车床的进给量,选择f =0.4 mm/r确定的进给量尚需满足机床进给机构的轻度要求,故需进行校验。根据表5-123,当钢料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 预计是进给力为760N修正系数 =1.0 =1.0 =1.17 故实际进给力为889.2N,满足要求。(c) 选择刀具磨钝标准及耐用度 根据表5-119,车刀后刀面的最大磨损量为1mm,可转位车刀耐用度T =30min (d) 确定切削速度V 根据表5-120,当用YT5硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系数为 = 0.8 = 0.65 =0.81 =1.15 = =1.0 故V = 1380.80.650.811.15 = 66m/minn = 1000v/d = 1000 67.8/3.14 21.2 = 954 r/min按CM6125车床的转速,选择 n = 1000 r/min (e) 校验机床功率 当钢料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min时, = 1.7KW切削功率的修正系数为=1.17 = = =1.0 =1.13 =0.8 =0.65故实际切削功率为 =0.72KW满足要求。最后确定的切削用量为 := 1 mm f = 0.4mm/r n = 1000r/min v = 66 m/min(2)粗车22.4mm外圆的切削用量所选刀具为YT5硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 90 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm (a) 确定背吃刀量 粗车双边余量为1.6mm 所以 = 0.8mm (b) 确定进给量f 根据表5-114,在粗车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm f= 0.4-0.5mm/r 按CM6125车床的进给量,选择f =0.4 mm/r确定的进给量尚需满足机床进给机构的轻度要求,故需进行校验。根据表5-123,当钢料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 预计是进给力为760N修正系数 =1.0 =1.0 =1.17 故实际进给力为889.2N,满足要求。(c) 选择刀具磨钝标准及耐用度 根据表5-119,车刀后刀面的最大磨损量为1mm,可转位车刀耐用度T =30min (d) 确定切削速度V 根据表5-120,当用YT5硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系数为 = 0.8 = 0.65 =0.81 =1.15 = =1.0 故V = 1380.80.650.811.15 = 66m/minn = 1000v/d = 1000 67.8/3.14 24 = 875 r/min按CM6125车床的转速,选择 n = 1000 r/min (e) 校验机床功率 当钢料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min时, = 1.7KW切削功率的修正系数为=1.17 = = =1.0 =1.13 =0.8 =0.65故实际切削功率为 =0.72KW满足要求。最后确定的切削用量为 := 1 mm f = 0.4mm/r n = 1000r/min v = 66 m/min(3)粗车端面的切削用量= 1.2 mm f = 0.2mm/r n = 1000r/min v = 66 m/min(4) 确定沟槽的切削用量 进给量f 手动 转速v = 630r/min工序2基本时间确定(a) 确定粗车19.2mm的外圆基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=20mm = 3mm = 0mm = 0 f = 0.4mm/r n= 16r/min i = 1所以Tj1= 4 S(b) 确定粗车22.4mm的外圆基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=82mm = 3mm = 0mm = 0 f = 0.4mm/r n= 16r/min i = 1所以Tj1= 14 S(c) 确定车端面的基本时间 Tj2 =i L/fn L = (dd1)/2 + + +d = 24mm = 2mm = 4mm = 0所以 Tj2 = 6S因此,总的基本时间为24S3 工序5切削用量确定(1)确定精车外圆17.2mm的切削用量。所选刀具为YT30硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 30 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm (a) 确定背吃刀量 粗车双边余量为0.9mm 所以 =0.45mm( b) 确定进给量f 根据表5-114,在精车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm , 按CM6125车床的进给量,选择f =0.2mm/r(c)速度V 根据表5-120,当用Y30硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系数为 = 0.8 = 1.4 =0.81 =1.15 = =1.0 故V = 1380.81.40.811.15 = 145m/minn = 1000v/d = 1000 67.8/3.14 18.1= 2549r/min按CM6125车床的转速,选择 n = 2500r/min 精车20mm外圆切削用量确定所选刀具为YT30硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 30 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm a 确定背吃刀量 粗车双边余量为0.9mm 所以 =0.45mm b 确定进给量f 根据表5-114,在精车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm , 按CM6125车床的进给量,选择f =0.2mm/rc 确定切削速度V 根据表5-120,当用Y30硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系数为 = 0.8 = 1.4 =0.81 =1.15 = =1.0 故V = 1380.81.40.811.15 = 145m/minn = 1000v/d = 1000 67.8/3.14 20.9= 2208r/min按CM6125车床的转速,选择 n = 2000r/min (2) 基本时间确定确定精车17.2mm的外圆基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=20mm = 0mm = 0mm = 0 f = 0.2mm/r n= 33r/min i = 1所以Tj1= 4 S确定精车20mm的外圆基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=82mm = 0mm = 0mm = 0 f = 0.2mm/r n= 33r/min i = 1所以Tj1= 13S因此 ,总的基本时间为15S (4) 工序6切削用量确定(1) 切削用量 本工序为粗车圆锥面。已知材料为45钢,= 670MPa,锻件,有外皮;机床为CM6125型卧式车床,工件装卡在三爪自定心卡盘中。确定粗车圆锥面的切削用量(以小端确定)。所选刀具为YT5硬质合金可转为车刀。选刀杆尺寸BH = 16mm 25mm ,刀片厚度为4.5mm。根据表5-113,选择车刀几何形状为卷屑槽倒淩型前刀面,前角=12 后角=6 ,主偏角= 90 ,副偏角 = 10 刃倾角 = 0 刀尖圆弧半径= 0.8mm a 确定背吃刀量 粗车双边余量为5.0mm 所以 = 2.5mm b 确定进给量f 根据表5-114,在粗车钢料,刀杆尺寸为16mm 25mm,小于等于3.0mm f= 0.4-0.5mm/r 按CM6125车床的进给量,选择f =0.4 mm/r确定的进给量尚需满足机床进给机构的轻度要求,故需进行校验。根据表5-123,当钢料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 预计是进给力为760N修正系数 =1.0 =1.0 =1.17 故实际进给力为889.2N,满足要求。c 选择刀具磨钝标准及耐用度 根据表5-119,车刀后刀面的最大磨损量为1mm,可转位车刀耐用度T =30min d 确定切削速度V 根据表5-120,当用YT5硬质合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 140m/min切削速度的修正系数为 = 0.8 = 0.65 =0.81 =1.15 = =1.0 故V = 1400.80.650.811.15 = 67.8m/minn = 1000v/d = 1000 67.8/3.14 41 = 526r/min按CM6125车床的转速,选择 n = 500 r/min e 校验机床功率 当钢料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min时, = 1.7KW切削功率的修正系数为=1.17 = = =1.0 =1.13 =0.8 =0.65故实际切削功率为 =0.72KW满足要求。最后确定的切削用量为 :=2.5 mm f = 0.4mm/r n = 500r/min v = 64.4m/min (2) 基本时间 确定粗车圆锥面的基本时间根据表2-21 ,车外圆的基本时间为Tj1= L i/fn = i(+ )/f n式中=20mm = 2mm = 3mm = 0 f = 0.4mm/r n= 8r/min i = 1所以Tj1= 8 S六 夹具设计 本夹具是工序11用麻花钻钻14,8.5孔的专用夹具,所设计的夹具装配图,供需简图及夹具体零件图如图所示。有关说明如下。(1) 定位方案 工件以 20的圆柱面及圆锥大端面为定位基准,采用V形块和平面的组合定位方案,两个V形块限制4个自由度,右边V形块的右端面限制一个自由度,共限制5个自由度。孔在圆周上无位置要求,该自由度不用限制。(2) 夹紧机构 根据生产率要求,运用手动夹紧可以满足。采用二位螺旋压板夹紧机构,拧紧螺母即可实现压紧,使用方便。压板夹紧力主要作用是防止工件在钻销力的作用下摆动和震动,手动螺旋夹紧是可靠的,可免去夹紧力计算。(3) 导引装置 为方便快捷的钻14 8.5两个孔,本夹具采用快换钻套,刀具在钻套的引导下准确的钻孔。(4) 夹具与机床的连接元件 采用10的定位销确定夹具与机床的相对正确位置,夹具体底座上开有两个U 形槽,用M14的螺栓固定在机床工作台上。(5) 夹具体 工件的定位元件,夹紧元件,导引装置用螺钉与夹具体底座连接起来,夹具体底座铸造加工出来,这样该夹具便有机连接起来,实现定位,夹紧,导引等功能。(6) 使用说明 安装工件时,松开右边铰链螺栓上的螺母,将两个铰链螺栓顺时针转动一个角度,然后将两块压板后撤,把工件放在V形块上,注意工件的圆锥大端面一定要紧贴在右边V 形块的右端面,实现可靠定位,然后把铰链螺栓放在铰链压板的U 形槽中,拧紧螺母实现可靠夹紧。(7) 结构特点 该夹具结构简单,操作方便。但斜面的制造误差以及V 形块在斜面上的安装误差,使孔的加工位置精度受到了限制,故适用于加工要求不高的场合。(8) 定位误差计算 工件采用V 形块定位,V 形块的定位误差= = 0.002692 因为斜面角度为15度,所以工件的水平方向的定位误差为y = 0.002692 sin(15)= 0.000696 ,满足定位要求。七 参考文献1、机械制造技术基础课程设计指南 主编: 崇凯 2、金属加工工艺及工装设计 主编: 黄如林 汪群3、工程图学 主编: 鲁屏宇4、机械制造装备设计 主编: 冯辛安 24 湖南工业大学 外文翻译专 业 机械设计制造及其自动化 学 生 姓 名 王 晓 雄 班 级 机本0303班 学 号 26030336 指 导 教 师 黄 开 友 MULTI-OBJECTIVE OPTIMAL FIXTURE LAYOUTDESIGN IN A DISCRETE DOMAINDiana Pelinescu and Michael Yu WangDepartment of Mechanical EngineeringUniversity of MarylandCollege Park, MD 20742 USAE-mail: yuwangeng.umd.eduAbstractThis paper addresses a major issue in fixture layout design:to evaluate the acceptable fixture designs based on several quality criteria and to select an optimal fixture appropriate with practical demands. The performance objectives considered are related to the fundamental requirements of kinematic localization and total fixturing (form-closure) and are defined as the workpiece localization accuracy and the norm and distribution of the locator contact forces. An efficient interchange algorithm is uaed in a multiple-criteria optimization process for different practical cases, leading to proper trade-off strategies for performing fixture synthesis.I. INTRODUCTIONProper fixture design is crucial to product quality in terms of precision and accuracy in part fabrication and assembly. Fixturing systems, usually consisting of clamps and locators, must be capable to assure certain quality performances, besides of positioning and holding the workpiece throughout all the machining operations. Although there are a few design guidelines such as 3-2-1 rule, automated systems for designing fixtures based on CAD models have been slow to evolve. This article describes a research approach to automated design of a class of fixtures for 3D workpieces. The parts considered to be fixtured present an arbitrary complex geometry, and the designed fixtures are limited to the minimum number of elements required, i.e. six locators and a clamp. Furthermore, the fixels are modeled as non-frictional point contacts and are restricted to be applied within a given collection of discrete candidate locations. In general, the set of fixture locations available is assumed to be a potentially very large collection; for example, the locations might be generated by discretizingthe exterior surfaces of the workpiece. The goal of the fixture design is to determine first, from the proposed discrete domain, the feasible fixture configurations that satisfy the form-closure constraint. Secondly, the sets of acceptable fixture designs are evaluated on several criteria and optimal fixtures are selected. The performance measures considered in this work are the localization accuracy, and the norm and distribution of the locator contact forces. These objectives cover the most critical error sources encountered in a fixture design, the position errors and the unwanted stress in the part-fixture elements due to an overloaded or unbalanced force system.The optimal fixture design approach is based on a concept of optimum experiment design. The algorithm developed evaluates efficiently the admissible designs exploiting the recursive properties in localization and force analysis. The algorithm produces the optimal fixture design that meets a set of multiple performance requirements.II. RELATED WORKLiterature on general fixturing techniques is substantial, e.g., 1. The essential requirement of fixturing is the century-old concept of form closure 2, which has beenextensively studied in the field of robotics in recent years 3, 4. There are several formal methods for analyzing performance of a given fixture based on the popular screw theory, dealing with issues such as kinematic closure 5, contact types and friction effects 6. A different analysis approach based on the geometric perturbation technique was reported in 7. An automatic modular fixture design procedure based on this method was developed in 8 to include geometric access constraints in addition to kinematic closure. The problem of designing modular fixtures gained more attention lately 9. There has also been extensive research in fixture designs, focusing on workpiece and fixture structuralrigidity 6, tool accessibility and path clearance 7. The problem of fixture synthesis has been largely studied for the case of a fixed number of fixture elements (or fixels) 8, 10, particularly in the application to robotic manipulation and grasping for its obvious easons 3, 4. This article aims to be an extension of the results on the fixture design issues previously reported in 14.III. FIXTURE MODELThe fundamental performance of a fixture is characterized by the kinematic constraints imposed on the workpiece being held by the fixture. The kinematic conditions are well understood 3, 4, 5, 7, 12. For a fixture of n locators (i = 1, 2, , n), the fixture can be represented by: dy=GTdqwhere define small perturbations in the locator positions and the location of the workpiece respectively. The fixture designis defined by the locator matrixi where and ni and ri denote the surface normal and position at the ith contact point on the workpiece surface. The problem of fixture design requires the synthesis of a fixturing scheme to meet a given set of performance requirements.IV. QUALITY PERFORMANCE CRITERIA FOR A FIXTUREA. Accurate LocalizationAn essential aspect of fixture quality is to position with precision the workpiece into the fixturing system. In general the workpiece positional errors are due to the geometric variability of the part and the locators set-up errors. This paper will focus only on the workpiece positional errors due to the locator positioning errors. As an extension of the fixture model equation (eq.1), the locator positioning errors dy can be related with the workpiece localization error dq as follows:Clearly, for given source errors the workpiece positional accuracy depends only on the locator locations being independent from the clamping system, the Fisher information matrix M = GGT characterizing completely the system errors. It has been shown 12 that a suitable criterion to achieve high localization accuracy is to maximize the determinant of the information matrix (Doptimality), i.e., max(det M).B. Minimal Locator Contact ForcesAnother objective in planning a fixture layout might be to minimize all support forces at the locator contact regions throughout all the operations with complete kinematic restraint or force-closure. Locator contact forces in response to the clamping action are given as: Normalizing these forces with respect to the clamping intensity we obtain:The force-closure condition requires these forces to be always positive for each locator i of a set of n locators:Computing the norm of the locator contact forces:leads to an appropriate design objective, i.e. minNote that this objective indicates both locator and clamp positions to be determined in the optimization process.C. Balanced Locator Contact ForcesAnother significant issue in designing a fixture is that the total force acting on the workpiece have to be distributed as uniformly as possible among the locator contactregions. If p represents the mean reactive force in response to the clamp action, then we define the dispersion of the locator contact forces as:Therefore, minimizing the defined dispersion represents an objective for a balanced force-closure: min(d).V. OPTIMAL FIXTURE DESIGN WITH INTERCHANGE ALGORITHMSAs mentioned earlier, by generating on the exterior surface of the workpiece to be fixtured a set of discrete locations defined as position and orientation, we create a potential collection for the fixture elements. For example, using the information contained in the part CAD model, a discrete vector collection (unitary, normal vectors) can be generated as uniformly as possible on those surfaces accessible to the fixture components (fig.1).Figure 1: Part CAD model and global collection of candidate locations for the fixture elements.The fixture design layout will select from this collection optimal candidates for locators and clamps with respect to the performance objectives and to the kinematic closure condition. Dealing with a large number of candidate locations the task of selecting an appropriate set of fixels is very complex.As already introduced in 12, 14 an effective method for finding the desired fixture with regard to one of the previous quality objectives is the optimal pursuit method with an interchange algorithm. Due to its own limitations and to the fact that the objectives are functions with many extremes, the exchange procedure may not end up to a unique optimized fixture configuration, but to several improved designs depending on the initial layout. Therefore the solution offered by the multiple interchange with random initialization algorithm is overwhelming favorable, fact that recommends this procedure over the single interchange algorithms. The algorithm can be described as a sequence of three phases:Phase 1: Random generation of initial sets of locators.The starting layout is generated by a random selection of distinct sets, each consisting from 6 locators out of the list of N candidate locations. If the clamp is pre-determined, avalid selection is obtained through a simultaneous check for all kinematic constraints. A big initial set of proposed ocators is preferred, giving the opportunity of finding a convergent optimal solution. However from the efficiency point of view the designer has to balance the algorithm between the accuracy of the final solution and the computation time.Phase 2: Improvement by interchange.The interchange algorithms goal is to pursue for an improvement of the initial sets of locators with respect to one of the objectives. Basically, this is done iteratively by exchanging one by one the proposed locators with candidate locations from the global collection. It is also essential to consider the form-closure restraint during the exchange procedure. The process will continue as long as an improvement of the objective function is registered. Studying the effect of interchange on the proposed quality measures leads us to some efficient algebraic properties. For example, an interchange between a current locator j (j = 1,2,6) and a candidate location k (k = 1,2, ,N-6) yields changes in the optimized function such that:Thus, at each interchange the pair is selected such that the significant term that controls the function evolution is improving, e.g. max p 2jk and min pc , easing the iterative process.Phase 3: Selecting the optimal solution.Applying the interchange algorithm for each initial set of locators we will end up with several distinct solutions on the configuration scheme of the fixture, the best fixture design corresponds evidently to the maximum improvement of the objective function. It should be emphasized that this algorithm can be used sequentially for different objective functions. Depending on the objective pursued the best solution can be evident (for a single objective) or might need the designers final decision (for multiple objectives).VI. MULTI-OBJECTIVE FIXTURE LOCATOR OPTIMIZATIONIn many applications the clamp is already fixed given some practical considerations. Then with the clamp predefined, the best fixture with respect to a certain performance criterion is constructed by selecting a suitable set of locators such that a significant improvement of the objective-function is registered. Using the random interchange algorithm we can analyze the impact of the optimization process on the fixture characteristics, as well as we can select the best optimized fixture solution for a specific criterion. In analyzing the effect of random interchange algorithm on several parts, there can be made the following statistical and empirical observations.A. Multi-objective trade-offsIn some applications both localization quality and a minimum force dispersion are important. In this case we may have to use a 2-step algorithm: first max(det M) and secondly min(d). The proposed order is a consequence of the above observations. First, maximizing the determinant will automatically decrease the dispersion. Next, a decreasing in dispersion leads in a decreasing in determinant value. Therefore, during the second phase of the algorithm tradeoffs between the two objectives occur. To solve the multi-objective optimization problem the interchange algorithm is applied successively for both objectives. With the clamp pre-defined, a rigorous check for form-closure is needed after each exchange step.A following set of plots present the results when the design requirements of precision localization and uniform contact forces are considered simultaneously. Fig. 2 and Fig. 3 illustrate the global changes of the fixture characteristics during the 2-step algorithm performed on an initial collection of distinct random sets of locators, with the clamp pre-fixed. It can be noticed the advantages of using max(det M) objective as a first step: while the determinant is increasing, the norm and the dispersion of the forces are decreasing, fact benefic for the overall quality of the fixture. Furthermore the solutions are convergent, such that the candidate set of locators for the next step will be significantly reduced. On the other hand, in the second phase, when applying min(d) optimization on sets of locators with a high determinant value the only trend in the determinant evolution is a decreasing one. Therefore, during the second phase of the algorithm tradeoffs between the two objectives occur, fact expressed also through the Pareto-line plot (Fig. 3). In this case the final decision has to be left for the designer to determine the best fixture scheme.Figure 2: Changes upon the fixture characteristics applying the 2-step optimization algorithm on an initial collection of random sets of locators.Figure 3: Behavior during a 2-step random interchange algorithm for a collection of locator sets.As an example, the behavior of a single initial set of locators is studied during the interchange processes of the 2-step algorithm (Fig. 4), confirming the previous remarks. The trade-off zone is decisive in the multiobjective design. The resultant configurations of the fixture after each successive phase are presented in Fig. 5. It can be noticed that the first objective moves the locators close to the boundaries as far as possible from each other, while the second one reorients them to the surfaces interior.Figure 4: General behavior of a 2-step interchange.Figure 5: Fixture configurations during a 2-step algorithm: (a) initial, (b) after max(det M), and (c) after min(d) respectively.B. Designer decision in finalizing the fixtureDuring the second phase of the algorithm a fairly significant decrease in the determinant value is registered, so few solutions will be acceptable for the multi-objective problem. In order to overcome these problems, an active designer control during min(d) interchange procedure is recommended. Essentially, the modifications consist in controlling the exchange procedure, such that the determinant of the improved locators must be permanently greater than a certain bound, simultaneously with the check for the form-closure condition. Even considering a tight bound for the determinant, more solutions are acceptable for the design than in the uncontrolled min(d) optimization case (fig. 6). As an example, the behavior of a single set of locators is studied during the interchange process of a 2- step algorithm controlled for two different bounds of the determinant value, emphasizing the fact that in the trade off zone the designer decision is decisive in finalizing the fixture configuration (fig. 7).Figure 6: Second phase of a 2-step random interchange algorithm: uncontrolled min(d); controlled min(d).Figure 7: General behavior during a 2-step algorithm applied on a single set of locators. (a) for B1 and (b) for B2.VII. OPTIMAL FIXTURE CLAMPINGThis section deals with a more complicated problem: to search simultaneously for the optimal clamp and locators in order to achieve a required fixture quality. Varying theclamp, it is obvious that the number of combinations for possible clamp-locators candidates is increasing very much. It will be shown that this problem is manageablefor the precise localization objective. For the other objectives we will have to restrain the search of the optimal clamp inside of a small set of proposed locations, such that the optimization procedure could be handled.A. Optimal Clamp from a Set of ClampsIn some applications the clamps have certain preferred locations, therefore the need to choose the best clamp from a proposed collection might be raised. For example, lets consider that a collection of preferred clamps is given, and an optimal fixture design with respect to the highly precise localization objective is needed. It is obvious that applying a random interchange procedure successively for each clamp, we find optimal fixture configurations for each specified clamp. Comparing the determinant values offered by these fixture schemes (fig. 8), we end up by selecting an optimal clamp and its corresponding locators, constructing the best- improved fixture design (fig. 9).Figure 8: Clamp selection from a collection of clamps for single-objective design.Figure 9: The initial collection of proposed clamps; the best clamp and the corresponding locators.B. Optimal Clamp from a Set of ClampsFurthermore, by extension, the selection of the optimal clamp from a set of proposed locations with regard to the multi-objective design problem can be considered. It consists of mainly applying the random 2-step interchange algorithm consecutively for each proposed clamp.By collecting the results after applying this procedure for all the clamps, we can compare their different behavior, and select the most appropriate one. It is obvious that an optimal clamp allows only small fluctuations of the determinant while the force dispersion is decreasing significantly (fig. 10). As an example, Fig. 11 illustrates the final fixture design consisting of the best clamp selected from a proposed collection with respect to the multi-objectives and the corresponding optimal locators.Figure 11: The initial collection of proposed clamps; the best clamp and the corresponding locators.VIII. CONCLUSIONSThis article focuses on optimal design of fixture layout for 3D workpieces with an optimal random interchange algorithm. The quality objectives considered include accurate workpiece localization, minimal and balanced contact forces. The paper focuses on multi-criteria optimal design with a hierarchical approach and a combined-objective approach. The optimization processes make use of an efficient interchange algorithm. Examples are used to illustrate empirical observations with respect to the design approaches and their effectiveness. The work described here is yet complete. Since the inter-relationship between the locators and the clamps has a determinant role on the fixture quality measures, a more coherent and complete approach to study the influence of the clamp and search of the optimal clamp position is needed in future works.IX. REFERENCES1 P. D. Campbell, Basic Fixture Design. New York: Industrial Press, 1994. 2 F. Reuleaux, The Kinematics of Machinery. Dover Publications, 1963.3 B. Mishra, J. T. Schwartz, and M. Sharir, On the existence and synthesis of multifinger positive grips, Robotics Report 89, Courant Institute of Mathematical Sciences, New York University, 1986.4 X. Markenscoff, L. Ni, and C. H. Papadimitriou, The geometry of grasping, International Journal of Robotics Research, vol. 9, no. 1, pp. 61-74, 1990.5 Y.-C. Chou, V. Chandru, and M. M. Barash, A mathematical approach to automate
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