CA6140手柄軸的加工工藝及夾具設計【鉆8.5螺紋孔】【說明書+CAD】

CA6140手柄軸的加工工藝及夾具設計【鉆8.5螺紋孔】【說明書+CAD】,鉆8.5螺紋孔,說明書+CAD,CA6140手柄軸的加工工藝及夾具設計【鉆8.5螺紋孔】【說明書+CAD】,ca6140,手柄,加工,工藝,夾具,設計,螺紋,羅紋,說明書,仿單,cad 機械加工工藝過程卡片機械加工工藝過程卡片產(chǎn)品型號CA6140零（部件）圖號產(chǎn)品名稱車床零（部件）名稱共一頁第一頁材料牌號45鋼毛坯種類模鍛件毛坯外型尺寸44mm126mm每毛坯可制件數(shù)1每臺件數(shù)1備注工序號工序名稱工序內(nèi)容車間工段設備工藝裝備工時/s準終單件正火2粗車粗車小端面；粗車外圓17.2mm，20mm；粗車溝槽3mm2.15mm，車溝槽1.5mm1mm，3mm0.5mmCM6125機床三爪自定心卡盤1073粗車粗車大端面及41mm的外圓CM6125機床三爪自定心卡盤1194半精車半精車小端面，半精車外圓17.2mm，20mm，半精車溝槽3mm2.15mm，車倒角CM6125機床三爪自定心卡盤1205精車精車外圓17.2mm，20mmCM6125機床三爪自定心卡盤1156粗車粗車圓錐面CM6125機床三爪自定心卡盤1367半精車半精車圓錐面CM6125機床三爪自定心卡盤頂1158精車精車圓錐面CM6125機床三爪自定心卡盤1569拋光圓錐面拋光18510鍍鉻圓錐面鍍鉻13211鉆孔鉆14mm ，8.5mm的孔Z518鉆床專用夾具10512擴孔擴14mm ，8.5mm的孔Z518鉆床專用夾具18013攻螺紋攻M10螺紋專用夾具11814粗銑粗銑鍵槽5mm3mm14mmX62臥式銑床專用夾具16915半精銑半精銑5mm3mm14mmX62臥式銑床專用夾具12816去毛刺去除全部毛刺鉗工臺17終檢按零件圖樣要求全面檢查機械加工工序2卡片機械加工工序卡片產(chǎn)品型號CA6140零（部件）圖號手柄軸產(chǎn)品名稱車床零（部件）名稱 第一頁車間工序號工序名材料牌號2粗車45鋼毛坯種類毛坯外型尺寸每毛坯可制件數(shù)每件臺數(shù)模鍛件44mm126mm11設備名稱設備型號設備編號同時加工件數(shù)臥式車床CM61251夾具編號夾具名稱切削液三爪自定心卡盤， 工位器具編號工位器具名稱工序時間/s準終單件119工序步 工步內(nèi)容工藝裝備主軸轉速/r.s-1切削速度/m.s-1進給量/mm.r-1背吃刀量/mm進給次數(shù)工步工時/s機動輔助 1 車小端面，保持尺寸mmYT5 90偏刀，游標卡尺161.10.21.516 2 車外圓19.2mm171.10.4114 3 車外圓 mm171.10.40.8114 4 車溝槽保持尺寸3mm2，775mm,及 61.5mm100.58手動0.715車溝槽保持尺寸1.5mm1mm 及 3mm100.58手動16車溝槽保持尺寸3mm0.5mm及 20.5mm,102.5mm100.58手動1機械加工工序5卡片機械加工工序卡片產(chǎn)品型號CA6140零（部件）圖號產(chǎn)品名稱車床零（部件）名稱 第一頁車間工序號工序名材料牌號5粗車45鋼毛坯種類毛坯外型尺寸每毛坯可制件數(shù)每件臺數(shù)模鍛件44mm126mm11設備名稱設備型號設備編號同時加工件數(shù)臥式車床CM61251夾具編號夾具名稱切削液三爪自定心卡盤工位器具編號工位器具名稱工序時間/s準終單件119工序步 工步內(nèi)容工藝裝備主軸轉速/r.s-1切削速度/m.s-1進給量/mm.r-1背吃刀量/mm進給次數(shù)工步工時/s機動輔助 1 精車外圓17.2mmYT30 90偏刀，游標卡尺402.030.20.4514 2 精車外圓mm332.030.20.45113 課 程 設 計 說 明 書 機械制造技術基礎設計題目：手柄軸（CA6140車床）的加工工藝鉆8.5螺紋孔的鉆床夾具設計學院：機械工程學院班級：機自0606學號：姓名： 指導：薛國祥老師題目：設計“手柄軸（CA6140車床）”零件的機械加工工藝規(guī)程及相關工序內(nèi)容：零件圖 1張 毛坯圖 1張 機械加工工藝過程卡片 1張 機械加工工序卡片 2張夾具裝配圖 1張夾具體零件圖 1張課程設計說明書 1份目錄一、 零件的工藝分析及生產(chǎn)類型的確定1. 零件的作用- 3 2. 熱處理- 33. 零件的生產(chǎn)類型- 3二、選擇毛坯，確定毛坯尺寸，設計毛坯圖1.選擇毛坯- 32.確定機械加工余量、毛胚尺寸和公差- 33.確定機械加工余量- 44確定毛坯尺-45.確定毛坯尺寸公差-56.設計毛坯圖-5三、選擇加工方法，制定工藝路線1.定位基準的選擇-62.零件表面加工方法的選擇-63.制定工藝路線-6四、工序設計1.選擇加工設備與工藝裝備-82.確定工序尺寸-9五、確定切削用量及基本時間-11六、夾具設計-20七 參考文獻-22 一 零件的工藝分析及生產(chǎn)類型的確定1. 零件的工藝性分析 通過對該零件圖的重新繪制，知原圖樣的視圖正確，完整，尺寸，公差及技術要求齊全。該零件屬軸類回轉體零件，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難獲得。 表面粗糙度要求較高 需經(jīng)多次切削才能滿足要求，手柄處鍍鉻，在鍍鉻之前須進行拋光處理以使鍍鉻均勻。本零件的最難加工的地方就是在斜面上鉆孔，且要保證孔與鍵槽成，需要專用夾具。總體來說，本零件的工藝性較好。2. 零件的生產(chǎn)類型 依設計的題目知：生產(chǎn)綱領 N = 30000萬/年 ， 生產(chǎn)類型為大批大量生產(chǎn) 零件是機床CA6140的手柄軸，質量為0.445Kg.二 選擇毛坯，確定毛坯尺寸，設計毛坯圖1. 選擇毛坯該材料為45鋼。該零件在工作過程中則經(jīng)常承受交變載荷，因此應選用鍛件，以使金屬纖維盡量不被切斷，保證零件工作可靠。零件屬批量生產(chǎn)，而且零件的輪廓尺寸不大，故采用摸鍛成型。這從提高生產(chǎn)率，保證加工精度上考慮，也是應該的。2確定機械加工余量，毛坯尺寸和公差鋼質摸鍛件的公差及機械加工余量按GB/T12362-2003確定。要確定毛坯尺寸公差及機械加工余量，應先確定如下各項因素。（1） 鍛件公差等級 由該零件的功用和技術要求，確定其鍛件公差等級為普通級。（2） 鍛件質量Mf 根據(jù)零件0.445kg,估算為mf=1.0kg.（3） 鍛件形狀復雜系數(shù)S S=Mf/Mn 該鍛件為圓形，假設其最大直徑為46mm,長126mm Mn = 1.6kg S = 1/1.6 = 0.62故該零件的形狀復雜系數(shù)S屬S2級。（4） 鍛件材質系數(shù)M 由于該零件材料為45鋼，是碳的質量分數(shù)小于0.65%的碳素鋼，故該鍛件的材質系數(shù)屬M1級。（5） 零件表面粗糙度 由零件圖可知，除17.2mm, 15.7mm 粗糙度Ra = 1.6,圓錐面處Ra=0.8，其余均為6.3。 3. 確定機械加工余量 根據(jù)鍛件質量，零件表面粗糙度，形狀復雜系數(shù)查表5-9，由此得單邊余量在厚度方向為1.7-2.2mm，水平方向亦為1.7-2.2mm，即鍛件各外徑的單面余量為1.7-2.2mm，各軸向尺寸的單面余量為1.7-2.2mm。 4 確定毛坯尺寸 上面查的加工余量適用于機械加工表面粗糙度Ra大于等于1.6m。Ra小于1.6m的表面，余量要適當加大。分析本零件，除17.2mm, 15.7mm 粗糙度Ra = 1.6, 其余均為6.3，因此這些表面的毛坯尺寸只需將零件的尺寸加上所查的余量即可。綜上所述，確定毛坯尺寸見下表 手柄軸毛坯（鍛件）尺寸零件尺寸單面加工余量鍛件尺寸17.2221.2224大端40圓錐面2445. 確定毛坯尺寸公差毛坯尺寸公差根據(jù)鍛件質量，材質系數(shù)，形狀復雜系數(shù)從表5-6，表5-7中查的。本零件毛坯尺寸允許偏差見下表 手柄軸毛坯（鍛件）尺寸允許偏差鍛件尺寸偏差根據(jù)21.2 表5-6244422表5-7102126 6 設計毛坯圖（1） 確定圓角半徑 鍛件的外圓角半徑按表5-12確定，內(nèi)圓角半徑按表5-13確定。分析本鍛件可確定外圓角R2, R3內(nèi)圓角R3(2) 確定模鍛斜度 按表5-11，外模鍛斜度= 3（3）確定分模位置由于毛坯為軸類鍛件，應采取軸向分模。為了便于起模及便于發(fā)現(xiàn)上，下模在模鍛過程中的錯移，選擇最大直徑即圓錐面處的對稱平面為分模面，分模線為直線，屬平直分模線。（4）確定毛坯的熱處理方式鋼質毛坯經(jīng)鍛造后應安排正火，以消除殘余的鍛造應力，并使不均勻的金相組織通過重新結晶而得到細化，均勻的組織，從而改善加工性。三 選擇加工方法，制定工藝路線1.定位基準的選擇以44的外圓和端面為粗基準，以17.2的外圓和端面為精基準。2.零件表面加工方法的選擇本零件的加工面有外圓，端面，鍵槽，倒角，倒圓，溝槽，錐面，孔，螺紋。（1）17.2的外圓面，未標注公差尺寸，表面粗糙度Ra 1.6，需要粗車，半精車，精車（2）20的外圓，公差等級IT6，需要粗車，半精車，精車。（3）圓錐面，為保證鍍鉻均勻，在鍍鉻之前圓錐面需要粗車，半精車，精車，保證Ra = 1.6 然后拋光。（4）槽3x2.15 表面粗糙度為Ra3.2,需要粗車，半精車 槽1.5x1 表面粗糙度為Ra6.3,粗車即可。 槽3x0.5 表面粗糙度為Ra6.3,粗車即可(5) 兩孔的表面粗糙度Ra6.3 需鉆，擴（6）鍵槽5314 粗糙度Ra6.3 需要粗銑，半精銑。（7）端面 本零件為回轉體端面，尺寸精度要求不高，所以大端面粗車即可滿足要求，但是小端面作為精基準應該粗車，半精車3制定工藝路線方案一工序1 正火工序2 以20mm處的外圓及端面定位，車大端面，粗車41的外圓工序3 以粗車后的40mm處外圓面及端面定位，粗車另一端面，粗車17.2mm的外圓，粗車20mm的外圓，車1.5mm1mm溝槽，粗車3mm0.5mm溝槽，粗車3mm2.15mm溝槽工序4 以粗車的20mm的外圓及端面定位 ，半精車，精車40mm的外圓。工序5 以精車后的40mm的外圓及端面定位，半精車，17.2mm的外圓，半精車20mm的外圓，半精車3mm2.15mm的溝槽工序6 精車17.2mm的外圓，精車20mm的外圓，車倒角。工序7 以20mm的外圓定位，粗車，半精車，精車圓錐面。工序8 粗銑，半精銑鍵槽工序9 拋光工序10 鍍鉻工序11 鉆，擴14mm孔及 8.5mm的螺紋孔工序12 攻螺紋工序13 去毛刺工序14 終檢 方案 二工序1 正火工序2 粗車小端面，粗車17.2mm的外圓，粗車20mm的外圓粗車，車1.5mmx1mm溝槽，粗車3mmx0.5mm溝槽，粗車3mm2.15mm溝槽工序3 粗車大端面及41mm的外圓工序4 半精車小端面，半精車，17.2mm的外圓，半精車20mm的外圓，半精車3mm2.15mm的溝槽，車倒角工序5 精車17.2mm的外圓，精車20mm的外圓工序6 以加工過的20mm外圓及端面定位，粗車圓錐面工序7 半精車圓錐面工序8 精車圓錐面工序9 拋光工序10 鍍鉻工序11 鉆14mm的孔和8.5mm的螺紋孔工序12 擴14mm的孔和8.5mm的螺紋孔工序13 攻M10的螺紋工序14 以20mm圓柱面及端面定位銑鍵槽5mm3mm14mm工序15 去毛刺工序16 終檢方案比較：方案二比方案一更容易保證尺寸精度，方案二以車過的41mm的外圓定位保證了定位精度，方案一的小端面知粗車一次可能不能保證要求的表面粗糙度，方案一的粗加工，精加工拍的比較混亂，不符合加工要求。 綜上所述，工藝路線應選擇方案二。四 工序設計1 選擇加工設備與工藝裝備（1） 選擇機床 根據(jù)不同的工序選擇機床。a 工序1-8是粗車合半精車。各工序的工步數(shù)不多，成批生產(chǎn)不要求很高的生產(chǎn)率，故選用臥式車床就能滿足要求。本零件外廓尺寸不大，精度要求不是很高，選CM6125即可。b 工序11 鉆孔，可采用專用夾具在立式鉆床上加工，故選Z525型立式鉆床。c 工序14是用整體硬質合金直柄立銑刀粗銑，半精銑鍵槽，用選用臥式銑床?？紤]本零件屬成批生產(chǎn)，所選機床使用范圍較廣為宜，故選常用的X62型銑床能滿足加工要求。d 工序13攻螺紋，需要絲錐。 ( 2 ) 選擇夾具本零件處粗銑及半精銑槽，鉆孔等工序需要專用夾具外，其他工序使用通用夾具即可，選用三抓自定心卡盤。（3） 選擇刀具 根據(jù)不同的工序選擇刀具 A 在車床上的加工工序，一般選用硬質合金車刀。加工鋼質零件采用YT類硬質合金，粗加工用YT5，半精加工用YT15，精加工用YT30.為提高生產(chǎn)率及經(jīng)濟性，應選用可轉位車刀（GB5343.1-1985,GB5343.2-1985）. B 銑刀按表5-104選直柄鍵槽銑刀鍵槽bxh=5mmx3mm,半精銑銑刀選擇直徑d = 5 mm l = 8mm L = 52mm由于粗銑后寬度方向單邊余量1mm，故粗銑時的銑刀選擇d=3mm l =5mm L =37mm C 鉆頭的選擇(a) 14mm的孔 擴孔選擇直柄擴孔鉆 d = 14mm,L =160mm l=108mm鉆孔是直徑方向的余量4mm，所以鉆孔時選擇直柄麻花鉆d = 13mm l= 151mm l1 = 101mm(b) 8.5mm的孔 擴孔選擇直柄擴孔鉆d = 8.8mm L=125mm l =81mm鉆孔時直徑方向余量1.5 mm ,選用直柄麻花鉆 d =7mm l =109mm l1=69mm（4） 選擇量具本零件屬成批生產(chǎn)，一般情況下盡量采用通用量具。根據(jù)零件表面的精度要求，尺寸和形狀特點，選擇如下。a 選擇外圓量具 外圓可選用讀數(shù)值0.02，測量范圍0150游標卡尺（表5-108）b 選擇加工軸向尺寸所用量具 軸向尺寸所用量具可選用讀數(shù)值0.05，測量范圍0150游標卡尺（表5-108）選擇加工槽所用量具c 選擇加工槽所用量具 槽經(jīng)粗銑，半精銑兩次加工。槽寬及槽深的尺寸公差的等級為：粗銑時均為IT14；半精銑時 ，槽寬IT13，槽深為IT14.。均可選用讀數(shù)值為0.02mm，測量范圍0150mm的游標卡尺進行測量。2 確定工序尺寸（1）確定圓柱面的工序尺寸 圓柱面多次加工的工序至于加工余量有關。本零件個圓柱表面的工序加工余量，工序尺寸及公差，表面粗糙度見下表 圓柱表面的工序加工余量，工序尺寸及公差，表面粗糙度 /mm加工表面工序雙邊余量工序尺寸及公差表面粗糙度及經(jīng)濟加工精度粗車半精車精車粗車半精車精車粗車半精車精車17.2mm外圓21.10.917.2IT13Ra 6.3IT11Ra 3.2IT6Ra 1.620g6mm外圓1.61.50.9IT13Ra 6.3IT11Ra 3.2IT6Ra 1.641mm外圓3_41_IT13Ra 6.3_（2） 確定各孔的工序尺寸加工對象工序雙邊余量工序尺寸及公差鉆擴鉆擴14mm孔1318.5mm孔71.5 （3） 確定各端面工序加工余量 /mm工序加工表面總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） 確定軸向尺寸 a 第一段17.2mm的長度L1，由尺寸鏈可得 L1 = 2mmb 第二段17.2mm的長度L2，求解尺寸鏈可得 L2 = 12.5mm c 第二段20mmm的長度L3，由尺寸鏈可得 L3 = d 圓錐面處的軸向長度L4， 由尺寸鏈可得 L4 = (5) 確定銑槽的工序尺寸 半精銑即可達到零件圖樣的要求，槽寬5mm, 粗銑后半精銑的余量1.5mm, 所以粗銑的寬度工序尺寸3.5mm（6） 圓錐面拋光直徑余量 0.1mm五 確定切削用量及基本時間切削用量包括背吃刀量 ，進給量f和切削速度v。確定順序是先確定，f，再確定v。1. 工序3切削用量及基本時間的確定 （1） 切削用量 本工序為粗車（車端面和外圓）。已知材料為45鋼，= 670MPa,鍛件，有外皮；機床為CM6125型臥式車床，工件裝卡在三爪自定心卡盤中。確定粗車外圓41mm的切削用量。所選刀具為YT5硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 90 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm a 確定背吃刀量 粗車雙邊余量為3.0mm 所以 1.5mm b 確定進給量f 根據(jù)表5-114，在粗車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm f= 0.4-0.5mm/r 按CM6125車床的進給量，選擇f =0.4 mm/r確定的進給量尚需滿足機床進給機構的輕度要求，故需進行校驗。根據(jù)表5-123，當鋼料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 預計是進給力為760N修正系數(shù) =1.0 =1.0 =1.17 故實際進給力為889.2N，滿足要求。c 選擇刀具磨鈍標準及耐用度 根據(jù)表5-119，車刀后刀面的最大磨損量為1mm，可轉位車刀耐用度T =30min d 確定切削速度V 根據(jù)表5-120，當用YT5硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 140m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 500 r/min e 校驗機床功率 當鋼料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min時， = 1.7KW切削功率的修正系數(shù)為=1.17 = = =1.0 =1.13 =0.8 =0.65故實際切削功率為 =0.72KW滿足要求。最后確定的切削用量為 ：= 1.5 mm f = 0.4mm/r n = 480r/min v = 66.3 m/min (2) 基本時間 a 確定粗車41mm的外圓基本時間根據(jù)表2-21 ，車外圓的基本時間為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 確定車端面的基本時間 Tj2 =i L/fn L = (dd1) + + + d = 44mm = 2mm = 4mm = 0所以 Tj2 = 18S因此，總的切削基本時間為26S. 2 工序2切削用量確定（1） 確定粗車19.2mm 外圓的切削用量所選刀具為YT5硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 90 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm （a） 確定背吃刀量 粗車雙邊余量為2mm 所以 = 1mm （b ） 確定進給量f 根據(jù)表5-114，在粗車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm f= 0.4-0.5mm/r 按CM6125車床的進給量，選擇f =0.4 mm/r確定的進給量尚需滿足機床進給機構的輕度要求，故需進行校驗。根據(jù)表5-123，當鋼料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 預計是進給力為760N修正系數(shù) =1.0 =1.0 =1.17 故實際進給力為889.2N，滿足要求。（c） 選擇刀具磨鈍標準及耐用度 根據(jù)表5-119，車刀后刀面的最大磨損量為1mm，可轉位車刀耐用度T =30min （d） 確定切削速度V 根據(jù)表5-120，當用YT5硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 1000 r/min （e） 校驗機床功率 當鋼料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min時， = 1.7KW切削功率的修正系數(shù)為=1.17 = = =1.0 =1.13 =0.8 =0.65故實際切削功率為 =0.72KW滿足要求。最后確定的切削用量為 ：= 1 mm f = 0.4mm/r n = 1000r/min v = 66 m/min（2）粗車22.4mm外圓的切削用量所選刀具為YT5硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 90 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm （a） 確定背吃刀量 粗車雙邊余量為1.6mm 所以 = 0.8mm （b） 確定進給量f 根據(jù)表5-114，在粗車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm f= 0.4-0.5mm/r 按CM6125車床的進給量，選擇f =0.4 mm/r確定的進給量尚需滿足機床進給機構的輕度要求，故需進行校驗。根據(jù)表5-123，當鋼料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 預計是進給力為760N修正系數(shù) =1.0 =1.0 =1.17 故實際進給力為889.2N，滿足要求。（c） 選擇刀具磨鈍標準及耐用度 根據(jù)表5-119，車刀后刀面的最大磨損量為1mm，可轉位車刀耐用度T =30min （d） 確定切削速度V 根據(jù)表5-120，當用YT5硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 1000 r/min （e） 校驗機床功率 當鋼料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min時， = 1.7KW切削功率的修正系數(shù)為=1.17 = = =1.0 =1.13 =0.8 =0.65故實際切削功率為 =0.72KW滿足要求。最后確定的切削用量為 ：= 1 mm f = 0.4mm/r n = 1000r/min v = 66 m/min（3）粗車端面的切削用量= 1.2 mm f = 0.2mm/r n = 1000r/min v = 66 m/min（4） 確定溝槽的切削用量 進給量f 手動 轉速v = 630r/min工序2基本時間確定(a) 確定粗車19.2mm的外圓基本時間根據(jù)表2-21 ，車外圓的基本時間為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) 確定粗車22.4mm的外圓基本時間根據(jù)表2-21 ，車外圓的基本時間為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) 確定車端面的基本時間 Tj2 =i L/fn L = (dd1)/2 + + +d = 24mm = 2mm = 4mm = 0所以 Tj2 = 6S因此，總的基本時間為24S3 工序5切削用量確定（1）確定精車外圓17.2mm的切削用量。所選刀具為YT30硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 30 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm (a) 確定背吃刀量 粗車雙邊余量為0.9mm 所以 =0.45mm( b) 確定進給量f 根據(jù)表5-114，在精車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm ， 按CM6125車床的進給量，選擇f =0.2mm/r(c)速度V 根據(jù)表5-120，當用Y30硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 2500r/min 精車20mm外圓切削用量確定所選刀具為YT30硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 30 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm a 確定背吃刀量 粗車雙邊余量為0.9mm 所以 =0.45mm b 確定進給量f 根據(jù)表5-114，在精車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm ， 按CM6125車床的進給量，選擇f =0.2mm/rc 確定切削速度V 根據(jù)表5-120，當用Y30硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 138m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 2000r/min （2） 基本時間確定確定精車17.2mm的外圓基本時間根據(jù)表2-21 ，車外圓的基本時間為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確定精車20mm的外圓基本時間根據(jù)表2-21 ，車外圓的基本時間為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 ，總的基本時間為15S (4) 工序6切削用量確定（1） 切削用量 本工序為粗車圓錐面。已知材料為45鋼，= 670MPa,鍛件，有外皮；機床為CM6125型臥式車床，工件裝卡在三爪自定心卡盤中。確定粗車圓錐面的切削用量（以小端確定）。所選刀具為YT5硬質合金可轉為車刀。選刀桿尺寸BH = 16mm 25mm ,刀片厚度為4.5mm。根據(jù)表5-113，選擇車刀幾何形狀為卷屑槽倒淩型前刀面，前角=12 后角=6 ，主偏角= 90 ，副偏角 = 10 刃傾角 = 0 刀尖圓弧半徑= 0.8mm a 確定背吃刀量 粗車雙邊余量為5.0mm 所以 = 2.5mm b 確定進給量f 根據(jù)表5-114，在粗車鋼料，刀桿尺寸為16mm 25mm，小于等于3.0mm f= 0.4-0.5mm/r 按CM6125車床的進給量，選擇f =0.4 mm/r確定的進給量尚需滿足機床進給機構的輕度要求，故需進行校驗。根據(jù)表5-123，當鋼料= 570670MPa , =2mm ,f= 0.75mm/r = 45 v = 65m/min 預計是進給力為760N修正系數(shù) =1.0 =1.0 =1.17 故實際進給力為889.2N，滿足要求。c 選擇刀具磨鈍標準及耐用度 根據(jù)表5-119，車刀后刀面的最大磨損量為1mm，可轉位車刀耐用度T =30min d 確定切削速度V 根據(jù)表5-120，當用YT5硬質合金刀具加工= 570670MPa , =3mm ,f= 0.75mm/r 切削速度V = 140m/min切削速度的修正系數(shù)為 = 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車床的轉速，選擇 n = 500 r/min e 校驗機床功率 當鋼料= 570670MPa , =2mm ,f= 0.75mm/r v = 46m/min時， = 1.7KW切削功率的修正系數(shù)為=1.17 = = =1.0 =1.13 =0.8 =0.65故實際切削功率為 =0.72KW滿足要求。最后確定的切削用量為 ：=2.5 mm f = 0.4mm/r n = 500r/min v = 64.4m/min (2) 基本時間 確定粗車圓錐面的基本時間根據(jù)表2-21 ，車外圓的基本時間為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 夾具設計 本夾具是工序11用麻花鉆鉆14，8.5孔的專用夾具，所設計的夾具裝配圖，供需簡圖及夾具體零件圖如圖所示。有關說明如下。（1） 定位方案 工件以 20的圓柱面及圓錐大端面為定位基準，采用V形塊和平面的組合定位方案，兩個V形塊限制4個自由度，右邊V形塊的右端面限制一個自由度，共限制5個自由度?？自趫A周上無位置要求，該自由度不用限制。（2） 夾緊機構 根據(jù)生產(chǎn)率要求，運用手動夾緊可以滿足。采用二位螺旋壓板夾緊機構，擰緊螺母即可實現(xiàn)壓緊，使用方便。壓板夾緊力主要作用是防止工件在鉆銷力的作用下擺動和震動，手動螺旋夾緊是可靠的，可免去夾緊力計算。（3） 導引裝置 為方便快捷的鉆14 8.5兩個孔，本夾具采用快換鉆套，刀具在鉆套的引導下準確的鉆孔。（4） 夾具與機床的連接元件 采用10的定位銷確定夾具與機床的相對正確位置，夾具體底座上開有兩個U 形槽，用M14的螺栓固定在機床工作臺上。（5） 夾具體 工件的定位元件，夾緊元件，導引裝置用螺釘與夾具體底座連接起來，夾具體底座鑄造加工出來，這樣該夾具便有機連接起來，實現(xiàn)定位，夾緊，導引等功能。（6） 使用說明 安裝工件時，松開右邊鉸鏈螺栓上的螺母，將兩個鉸鏈螺栓順時針轉動一個角度，然后將兩塊壓板后撤，把工件放在V形塊上，注意工件的圓錐大端面一定要緊貼在右邊V 形塊的右端面，實現(xiàn)可靠定位，然后把鉸鏈螺栓放在鉸鏈壓板的U 形槽中，擰緊螺母實現(xiàn)可靠夾緊。（7） 結構特點 該夾具結構簡單，操作方便。但斜面的制造誤差以及V 形塊在斜面上的安裝誤差，使孔的加工位置精度受到了限制，故適用于加工要求不高的場合。（8） 定位誤差計算 工件采用V 形塊定位，V 形塊的定位誤差= = 0.002692 因為斜面角度為15度，所以工件的水平方向的定位誤差為y = 0.002692 sin(15)= 0.000696 ,滿足定位要求。七 參考文獻1、機械制造技術基礎課程設計指南 主編： 崇凱 2、金屬加工工藝及工裝設計 主編： 黃如林 汪群3、工程圖學 主編： 魯屏宇4、機械制造裝備設計 主編： 馮辛安 24 湖南工業(yè)大學 外文翻譯專 業(yè) 機械設計制造及其自動化 學 生 姓 名 王 曉 雄 班 級 機本0303班 學 號 26030336 指 導 教 師 黃 開 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